Pub Date : 2022-11-15DOI: 10.3390/logistics6040079
Patrik Richnák
Background: The digital transformation towards Industry 4.0 has become a necessity for businesses as it makes them more flexible, agile and responsive. Logistics is no exception, as it is constantly undergoing a significant transformation supported by revolutionary Industry 4.0 technologies that are fundamentally changing logistics processes and operations. Methods: In the construction of the paper, the following classical scientific methods were used: analysis, synthesis, induction, deduction, analogy, specification and comparison. Among the special scientific methods, the method of classification, concretisation, graphical methods, questionnaire survey and statistical methods were used. Results: The analysed enterprises perceive digital transformation in logistics. In the analysed enterprises in Slovakia, the Industry 4.0 strategy is implemented in logistics. Industry 4.0 in logistics has the largest representation in production logistics in each enterprise category. In implementing Industry 4.0 in logistics, enterprises confront the biggest barrier, namely, investment costs. Conclusions: Through one-way analysis of variance (ANOVA) and Pearson’s correlation coefficient, several significant relationships were confirmed. The significant relationship between manufacturing logistics and selected Industry 4.0 technologies was demonstrated. The significant relationship between procurement logistics and selected Industry 4.0 technologies was also demonstrated. The statistical analysis also confirmed a significant relationship between distribution logistics and the selected Industry 4.0 technologies.
{"title":"Current Trend of Industry 4.0 in Logistics and Transformation of Logistics Processes Using Digital Technologies: An Empirical Study in the Slovak Republic","authors":"Patrik Richnák","doi":"10.3390/logistics6040079","DOIUrl":"https://doi.org/10.3390/logistics6040079","url":null,"abstract":"Background: The digital transformation towards Industry 4.0 has become a necessity for businesses as it makes them more flexible, agile and responsive. Logistics is no exception, as it is constantly undergoing a significant transformation supported by revolutionary Industry 4.0 technologies that are fundamentally changing logistics processes and operations. Methods: In the construction of the paper, the following classical scientific methods were used: analysis, synthesis, induction, deduction, analogy, specification and comparison. Among the special scientific methods, the method of classification, concretisation, graphical methods, questionnaire survey and statistical methods were used. Results: The analysed enterprises perceive digital transformation in logistics. In the analysed enterprises in Slovakia, the Industry 4.0 strategy is implemented in logistics. Industry 4.0 in logistics has the largest representation in production logistics in each enterprise category. In implementing Industry 4.0 in logistics, enterprises confront the biggest barrier, namely, investment costs. Conclusions: Through one-way analysis of variance (ANOVA) and Pearson’s correlation coefficient, several significant relationships were confirmed. The significant relationship between manufacturing logistics and selected Industry 4.0 technologies was demonstrated. The significant relationship between procurement logistics and selected Industry 4.0 technologies was also demonstrated. The statistical analysis also confirmed a significant relationship between distribution logistics and the selected Industry 4.0 technologies.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49615990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-11DOI: 10.3390/logistics6040078
Dhiordan Cunha Tadaiesky, Joaquim Lima das Neves Neto, A. C. S. Melo, R. Anholon, Eliane de Castro Coutinho, V. Martins
Background: The COVID-19 pandemic has moved the world in every way, directly impacting supply chains globally and bringing major challenges to management, decision-makers, and companies of all sizes and sectors. This intensifies when it comes to the Brazilian Amazon region, a place that historically already lives with several maintenance projects focused on supply chain management (SCM). Methods: Thus, this research aimed to understand the main challenges faced by professionals in the supply chain area in the Amazon region through the development of a survey with professionals in the area. This study conducted a structured questionnaire containing 10 challenges related to SCM during the pandemic period to generate a ranking of these challenges using data analysis using means and comparative ordering using the TOPSIS Multicriteria Technique. Results: It was observed that the most relevant challenges for companies in this region were, respectively, distribution, economic problems, and interruptions in supply and demand. These obstacles promote debates with the literature and foster the expansion of knowledge about the insertion of resilience elements in supply chains in the Amazon. Conclusions: From a theoretical point of view and because it is exploratory research, the results serve as a basis for researchers in the area who aim to understand and expand the debates on this topic through future research. From a practical point of view, the results can help supply chain managers in the Amazon region who work directly in its maintenance and aim to maintain its resilience, since they already have the main challenges for the proper functioning of supply chains identified and ranked. Because it is an exploratory study, the results achieved can contribute significantly to the expansion of debates in the area and in a practical way with managers involved in activities that compose supply chains.
{"title":"Challenges to Promoting Resilience in Supply Chains Observed during the COVID-19 Pandemic: An Exploratory Study of the Amazon Region Using the TOPSIS Technique","authors":"Dhiordan Cunha Tadaiesky, Joaquim Lima das Neves Neto, A. C. S. Melo, R. Anholon, Eliane de Castro Coutinho, V. Martins","doi":"10.3390/logistics6040078","DOIUrl":"https://doi.org/10.3390/logistics6040078","url":null,"abstract":"Background: The COVID-19 pandemic has moved the world in every way, directly impacting supply chains globally and bringing major challenges to management, decision-makers, and companies of all sizes and sectors. This intensifies when it comes to the Brazilian Amazon region, a place that historically already lives with several maintenance projects focused on supply chain management (SCM). Methods: Thus, this research aimed to understand the main challenges faced by professionals in the supply chain area in the Amazon region through the development of a survey with professionals in the area. This study conducted a structured questionnaire containing 10 challenges related to SCM during the pandemic period to generate a ranking of these challenges using data analysis using means and comparative ordering using the TOPSIS Multicriteria Technique. Results: It was observed that the most relevant challenges for companies in this region were, respectively, distribution, economic problems, and interruptions in supply and demand. These obstacles promote debates with the literature and foster the expansion of knowledge about the insertion of resilience elements in supply chains in the Amazon. Conclusions: From a theoretical point of view and because it is exploratory research, the results serve as a basis for researchers in the area who aim to understand and expand the debates on this topic through future research. From a practical point of view, the results can help supply chain managers in the Amazon region who work directly in its maintenance and aim to maintain its resilience, since they already have the main challenges for the proper functioning of supply chains identified and ranked. Because it is an exploratory study, the results achieved can contribute significantly to the expansion of debates in the area and in a practical way with managers involved in activities that compose supply chains.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41371940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-31DOI: 10.3390/logistics6040077
Marlies van Tilburg, H. Krikke, W. Lambrechts
Background: Despite growing popularity, Circular Economy has not reached its full potential. One of the frequently mentioned success factors is the adoption of a Circular Business Model. However, fueled by (too) many constraints, its implementation is often hampered by so-called vicious cycles. Successful Circular Business Models require intensive collaboration between buyers and suppliers, with one of the key questions remaining who takes the initiative and leads the development: buyer or supplier? Methods: Through a single case study combining desk research, interviews, participative observations and analysis of vicious cycles, we investigate how supply chain relationships managed by the supplier can enhance the implementation of Circular Business Models. Results: We show that supplier tactics can relax constraints and break vicious cycles through (1) buyer–supplier relationship management, (2) functional integration of stakeholders and (3) incentive management. We also show that, due to supplier captive conditions, a number of enabling factors are indispensable, namely: (1) the availability of buyer incentives; (2) (joint experimenting to develop) circular knowledge; (3) sharing clear visions on circularity; (4) being transparent in possibilities; and (5) supply chain leadership. Conclusions: As a consequence, strategic trust-based partnerships are a prerequisite for turning vicious cycles into virtuous cycles. Future research should also investigate the role of the buyer, including buyer captive conditions, and how to shape supply chain leadership. Finally, the role of supplier tactics in relation to other success factors next to Circular Business Models needs to be further explored.
{"title":"Supply Chain Relationships in Circular Business Models: Supplier Tactics at Royal Smit Transformers","authors":"Marlies van Tilburg, H. Krikke, W. Lambrechts","doi":"10.3390/logistics6040077","DOIUrl":"https://doi.org/10.3390/logistics6040077","url":null,"abstract":"Background: Despite growing popularity, Circular Economy has not reached its full potential. One of the frequently mentioned success factors is the adoption of a Circular Business Model. However, fueled by (too) many constraints, its implementation is often hampered by so-called vicious cycles. Successful Circular Business Models require intensive collaboration between buyers and suppliers, with one of the key questions remaining who takes the initiative and leads the development: buyer or supplier? Methods: Through a single case study combining desk research, interviews, participative observations and analysis of vicious cycles, we investigate how supply chain relationships managed by the supplier can enhance the implementation of Circular Business Models. Results: We show that supplier tactics can relax constraints and break vicious cycles through (1) buyer–supplier relationship management, (2) functional integration of stakeholders and (3) incentive management. We also show that, due to supplier captive conditions, a number of enabling factors are indispensable, namely: (1) the availability of buyer incentives; (2) (joint experimenting to develop) circular knowledge; (3) sharing clear visions on circularity; (4) being transparent in possibilities; and (5) supply chain leadership. Conclusions: As a consequence, strategic trust-based partnerships are a prerequisite for turning vicious cycles into virtuous cycles. Future research should also investigate the role of the buyer, including buyer captive conditions, and how to shape supply chain leadership. Finally, the role of supplier tactics in relation to other success factors next to Circular Business Models needs to be further explored.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42686557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-28DOI: 10.3390/logistics6040076
Alisha Lakra, Shubhkirti Gupta, Ravi Ranjan, S. Tripathy, D. Singhal
Background: Our day-to-day commodities truly depend on the industrial sector, which is expanding at a rapid rate along with the growing population. The production of goods needs to be accurate and rapid. Thus, for the present research, we have incorporated machine-learning (ML) technology in the manufacturing sector (MS). Methods: Through an inclusive study, we identify 11 factors within the research background that could be seen as holding significance for machine learning in the manufacturing sector. An interpretive structural modeling (ISM) method is used, and inputs from experts are applied to establish the relationships. Results: The findings from the ISM model show the ‘order fulfillment factor as the long-term focus and the ‘market demand’ factor as the short-term focus. The results indicate the critical factors that impact the development of machine learning in the manufacturing sector. Conclusions: Our research contributes to the manufacturing sector which aims to incorporate machine learning. Using the ISM model, industries can directly point out their oddities and improve on them for better performance.
{"title":"The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach","authors":"Alisha Lakra, Shubhkirti Gupta, Ravi Ranjan, S. Tripathy, D. Singhal","doi":"10.3390/logistics6040076","DOIUrl":"https://doi.org/10.3390/logistics6040076","url":null,"abstract":"Background: Our day-to-day commodities truly depend on the industrial sector, which is expanding at a rapid rate along with the growing population. The production of goods needs to be accurate and rapid. Thus, for the present research, we have incorporated machine-learning (ML) technology in the manufacturing sector (MS). Methods: Through an inclusive study, we identify 11 factors within the research background that could be seen as holding significance for machine learning in the manufacturing sector. An interpretive structural modeling (ISM) method is used, and inputs from experts are applied to establish the relationships. Results: The findings from the ISM model show the ‘order fulfillment factor as the long-term focus and the ‘market demand’ factor as the short-term focus. The results indicate the critical factors that impact the development of machine learning in the manufacturing sector. Conclusions: Our research contributes to the manufacturing sector which aims to incorporate machine learning. Using the ISM model, industries can directly point out their oddities and improve on them for better performance.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41303205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-18DOI: 10.3390/logistics6040075
Abdel-Nasser Sharkawy, Mustafa M. Ali
Background: Safety is the very necessary issue that must be considered during human-robot collaboration in the same workspace or area. Methods: In this manuscript, a nonlinear autoregressive model with an exog-enous inputs neural network (NARXNN) is developed for the detection of collisions between a manipulator and human. The design of the NARXNN depends on the dynamics of the manipulator’s joints and considers only the signals of the position sensors that are intrinsic to the manipulator’s joints. Therefore, this network could be applied and used with any conventional robot. The data used for training the designed NARXNN are generated by two experiments considering the sinusoidal joint motion of the manipulator. The first experiment is executed using a free-of-contact motion, whereas in the second experiment, random collisions by human hands are performed with the robot. The training process of the NARXNN is carried out using the Levenberg–Marquardt algorithm in MATLAB. The evaluation and the effectiveness (%) of the developed method are investigated taking into account different data and conditions from the used data for training. The experiments are executed using the KUKA LWR IV manipulator. Results: The results prove that the trained method is efficient in estimating the external joint torque and in correctly detecting the collisions. Conclusions: Eventually, a comparison is presented between the proposed NARXNN and the other NN architectures presented in our previous work.
{"title":"NARX Neural Network for Safe Human–Robot Collaboration Using Only Joint Position Sensor","authors":"Abdel-Nasser Sharkawy, Mustafa M. Ali","doi":"10.3390/logistics6040075","DOIUrl":"https://doi.org/10.3390/logistics6040075","url":null,"abstract":"Background: Safety is the very necessary issue that must be considered during human-robot collaboration in the same workspace or area. Methods: In this manuscript, a nonlinear autoregressive model with an exog-enous inputs neural network (NARXNN) is developed for the detection of collisions between a manipulator and human. The design of the NARXNN depends on the dynamics of the manipulator’s joints and considers only the signals of the position sensors that are intrinsic to the manipulator’s joints. Therefore, this network could be applied and used with any conventional robot. The data used for training the designed NARXNN are generated by two experiments considering the sinusoidal joint motion of the manipulator. The first experiment is executed using a free-of-contact motion, whereas in the second experiment, random collisions by human hands are performed with the robot. The training process of the NARXNN is carried out using the Levenberg–Marquardt algorithm in MATLAB. The evaluation and the effectiveness (%) of the developed method are investigated taking into account different data and conditions from the used data for training. The experiments are executed using the KUKA LWR IV manipulator. Results: The results prove that the trained method is efficient in estimating the external joint torque and in correctly detecting the collisions. Conclusions: Eventually, a comparison is presented between the proposed NARXNN and the other NN architectures presented in our previous work.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47883526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-17DOI: 10.3390/logistics6040074
Mohit Malik, V. Gahlawat, R. Mor, Vijay Dahiya, Mukheshwar Yadav
Background: The global dairy market is experiencing a massive transition as dairy farming has recently undergone modernization. As a result, the dairy industry needs to improve its operational efficiencies by implementing effective optimization techniques. Conventional and emerging optimization techniques have already gained momentum in the dairy industry. This study’s objective was to explore the optimization techniques developed for or implemented in the dairy supply chain (DSC) and to investigate how these techniques can improve the DSC. Methods: A systematic review approach based on PRISMA guidelines were adopted to conduct this review. The authors used descriptive statistics for statistical analysis. Results: Modernization has led the dairy industry to improve its operational efficiencies by implementing the most effective optimization techniques. Researchers have used mathematical modeling-based methods and are shifting to artificial intelligence (AI) and machine learning (ML) -based approaches in the DSC. The mathematical modeling-based techniques remain dominant (56% of articles), but AI and ML-based techniques are gaining traction (used in around 44% of articles). Conclusions: The review findings show insight into the benefits and implications of optimization techniques in the DSC. This research shows how optimization techniques are associated with every phase of the DSC and how new technologies have affected the supply chain.
{"title":"Application of Optimization Techniques in the Dairy Supply Chain: A Systematic Review","authors":"Mohit Malik, V. Gahlawat, R. Mor, Vijay Dahiya, Mukheshwar Yadav","doi":"10.3390/logistics6040074","DOIUrl":"https://doi.org/10.3390/logistics6040074","url":null,"abstract":"Background: The global dairy market is experiencing a massive transition as dairy farming has recently undergone modernization. As a result, the dairy industry needs to improve its operational efficiencies by implementing effective optimization techniques. Conventional and emerging optimization techniques have already gained momentum in the dairy industry. This study’s objective was to explore the optimization techniques developed for or implemented in the dairy supply chain (DSC) and to investigate how these techniques can improve the DSC. Methods: A systematic review approach based on PRISMA guidelines were adopted to conduct this review. The authors used descriptive statistics for statistical analysis. Results: Modernization has led the dairy industry to improve its operational efficiencies by implementing the most effective optimization techniques. Researchers have used mathematical modeling-based methods and are shifting to artificial intelligence (AI) and machine learning (ML) -based approaches in the DSC. The mathematical modeling-based techniques remain dominant (56% of articles), but AI and ML-based techniques are gaining traction (used in around 44% of articles). Conclusions: The review findings show insight into the benefits and implications of optimization techniques in the DSC. This research shows how optimization techniques are associated with every phase of the DSC and how new technologies have affected the supply chain.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44303275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.3390/logistics6040073
M. Görges, M. Freitag
Background: Automobile terminals play a key role in global finished car supply chains. Due to their connecting character between manufacturers on the one side and distributers on the other side, they are continuously faced with volatile demand fluctuations and unforeseen dynamic events, which cannot be handled adequately by existing planning methods. Autonomous control concepts already showed promising results coping with such dynamics. Methods: This paper describes the causes of dynamics and the terminal systems’ inherent shortcomings in dealing with such dynamics. On this basis, it derives terminal’s demand for novel planning approaches and presents a new integrated autonomous control method for automobile terminals. This novel autonomous control approach combines yard and berth assignments. This paper evaluates the performance of the new approach in a small comprehensive generic scenario. It compares classical planning approaches with the new autonomous control approach, by using a discrete event simulation model. Moreover, it analyses all relevant parameters of the new approach in a full factorial experiment design. In a second step this paper proves the applicability of the combined autonomous control approach to real-world terminals. It presents a simulation model of a real-world terminal and compares the new method with the existing terminal planning approaches. Results: This paper will show that the autonomous control approach is capable of outperforming existing centralized planning methods. In the generic and in the real-world case the new combined method leads to the best logistic target achievement. Conclusions: The new approach is highly suitable to automobile terminal systems and helps to overcome existing shortcomings. Especially in highly dynamic and complex settings, autonomous control performs better than conventional yard planning approaches.
{"title":"Design and Evaluation of an Integrated Autonomous Control Method for Automobile Terminals","authors":"M. Görges, M. Freitag","doi":"10.3390/logistics6040073","DOIUrl":"https://doi.org/10.3390/logistics6040073","url":null,"abstract":"Background: Automobile terminals play a key role in global finished car supply chains. Due to their connecting character between manufacturers on the one side and distributers on the other side, they are continuously faced with volatile demand fluctuations and unforeseen dynamic events, which cannot be handled adequately by existing planning methods. Autonomous control concepts already showed promising results coping with such dynamics. Methods: This paper describes the causes of dynamics and the terminal systems’ inherent shortcomings in dealing with such dynamics. On this basis, it derives terminal’s demand for novel planning approaches and presents a new integrated autonomous control method for automobile terminals. This novel autonomous control approach combines yard and berth assignments. This paper evaluates the performance of the new approach in a small comprehensive generic scenario. It compares classical planning approaches with the new autonomous control approach, by using a discrete event simulation model. Moreover, it analyses all relevant parameters of the new approach in a full factorial experiment design. In a second step this paper proves the applicability of the combined autonomous control approach to real-world terminals. It presents a simulation model of a real-world terminal and compares the new method with the existing terminal planning approaches. Results: This paper will show that the autonomous control approach is capable of outperforming existing centralized planning methods. In the generic and in the real-world case the new combined method leads to the best logistic target achievement. Conclusions: The new approach is highly suitable to automobile terminal systems and helps to overcome existing shortcomings. Especially in highly dynamic and complex settings, autonomous control performs better than conventional yard planning approaches.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41347272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.3390/logistics6040072
Chakat Chueadee, P. Kriengkorakot, Nuchsara Kriengkorakot
Background: This research aimed to establish a network linked to generation, for the transport route of tapioca starch products to a land port, serving as the logistics hub of Thailand’s Nakhon Ratchasima province. Methods: The adaptive large neighborhood search (ALNS) algorithm, combined with the differential evolution (DE) approach, was used for the problem analysis, and this method was named modified differential evolution adaptive large neighborhood search (MDEALNS) is a new method that includes six steps, which are (1) initialization, (2) mutation, (3) recombination, (4) updating with ALNS, (5) Selection and (6) repeat the (2) to (5) steps until the termination condition is met. The MDEALNS algorithm designed a logistics network linking the optimal route and a suitable open/close factory allocation with the lowest transport cost for tapioca starch. The operating supply chain of tapioca starch manufacturing in the case study. The proposed methods have been tested with datasets of the three groups of test instances and the case study consisted of 404 farms, 33 factories, and 1 land port. Results: The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS. Conclusions: The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS.
{"title":"MDEALNS for Solving the Tapioca Starch Logistics Network Problem for the Land Port of Nakhon Ratchasima Province, Thailand","authors":"Chakat Chueadee, P. Kriengkorakot, Nuchsara Kriengkorakot","doi":"10.3390/logistics6040072","DOIUrl":"https://doi.org/10.3390/logistics6040072","url":null,"abstract":"Background: This research aimed to establish a network linked to generation, for the transport route of tapioca starch products to a land port, serving as the logistics hub of Thailand’s Nakhon Ratchasima province. Methods: The adaptive large neighborhood search (ALNS) algorithm, combined with the differential evolution (DE) approach, was used for the problem analysis, and this method was named modified differential evolution adaptive large neighborhood search (MDEALNS) is a new method that includes six steps, which are (1) initialization, (2) mutation, (3) recombination, (4) updating with ALNS, (5) Selection and (6) repeat the (2) to (5) steps until the termination condition is met. The MDEALNS algorithm designed a logistics network linking the optimal route and a suitable open/close factory allocation with the lowest transport cost for tapioca starch. The operating supply chain of tapioca starch manufacturing in the case study. The proposed methods have been tested with datasets of the three groups of test instances and the case study consisted of 404 farms, 33 factories, and 1 land port. Results: The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS. Conclusions: The computational results show that MDEALNS method can reduced the distance and the fuel cost and outperformed the highest performance of the original method used by LINGO, DE, and ALNS.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41418551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-09DOI: 10.3390/logistics6040071
Sara Rye
Performance frameworks are common ways to guarantee the success of a collaboration by assessment/improvement of the organisations. However, collaborative performance in recurring collaborations (RC) and temporary ones (TC) are being measured differently due to their inherent characteristics. A systematic review of 282 existing studies, from 2000 onwards, into collaborative networks divided between RC and TC based on the duration of collaboration and the application of the studies was performed. The result gave rise to the thematic analysis of the textual narratives, as well as a quantitative meta-summary of the synthesis. The review shows two different approaches to guarantee the performance of the collaboration. The first group provide a recipe for success by recognizing the causal relationship between nine collaborative measures, including information and risk sharing, trust, commitment, agility, power balance, leadership, prior-experience, and alignment. The second group ensures the success of collaboration by selecting suitable partners based on their previous performance emerging through synergy, readiness, agility and internal–external factors. The reasoning behind these differences are discussed and the current gaps in research are outlined.
{"title":"Analysis of the Disparity between Recurring and Temporary Collaborative Performance: A Literature Review between 1994 and 2021","authors":"Sara Rye","doi":"10.3390/logistics6040071","DOIUrl":"https://doi.org/10.3390/logistics6040071","url":null,"abstract":"Performance frameworks are common ways to guarantee the success of a collaboration by assessment/improvement of the organisations. However, collaborative performance in recurring collaborations (RC) and temporary ones (TC) are being measured differently due to their inherent characteristics. A systematic review of 282 existing studies, from 2000 onwards, into collaborative networks divided between RC and TC based on the duration of collaboration and the application of the studies was performed. The result gave rise to the thematic analysis of the textual narratives, as well as a quantitative meta-summary of the synthesis. The review shows two different approaches to guarantee the performance of the collaboration. The first group provide a recipe for success by recognizing the causal relationship between nine collaborative measures, including information and risk sharing, trust, commitment, agility, power balance, leadership, prior-experience, and alignment. The second group ensures the success of collaboration by selecting suitable partners based on their previous performance emerging through synergy, readiness, agility and internal–external factors. The reasoning behind these differences are discussed and the current gaps in research are outlined.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45232350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.3390/logistics6040070
S. Fayezi
Background: In this essay, we address an important issue in the logistics education discourse relating to student-centered curriculum design and evaluation. Methods: We adopt an integrative approach based on conceptual development and guided by constructive alignment. Results: We apply and elaborate our conceptual framework using a case of a teaching plan in logistics management. We also propose an evaluation strategy for our teaching plan in the form of a template. Conclusions: Our essay contributes to the logistics education discourse by using learning theories and developing curriculum design and evaluation guidelines that can be replicated by other educators.
{"title":"Student-Centered Curriculum Design and Evaluation in Logistics Management","authors":"S. Fayezi","doi":"10.3390/logistics6040070","DOIUrl":"https://doi.org/10.3390/logistics6040070","url":null,"abstract":"Background: In this essay, we address an important issue in the logistics education discourse relating to student-centered curriculum design and evaluation. Methods: We adopt an integrative approach based on conceptual development and guided by constructive alignment. Results: We apply and elaborate our conceptual framework using a case of a teaching plan in logistics management. We also propose an evaluation strategy for our teaching plan in the form of a template. Conclusions: Our essay contributes to the logistics education discourse by using learning theories and developing curriculum design and evaluation guidelines that can be replicated by other educators.","PeriodicalId":56264,"journal":{"name":"Logistics-Basel","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45358369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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