Pub Date : 2023-05-30DOI: 10.1080/17509653.2023.2219644
R. Corsini, A. Costa, J. Framiñan
{"title":"An adaptive product changeover policy for a capacitated two-product supply chain in a non-stationary demand environment","authors":"R. Corsini, A. Costa, J. Framiñan","doi":"10.1080/17509653.2023.2219644","DOIUrl":"https://doi.org/10.1080/17509653.2023.2219644","url":null,"abstract":"","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45923925","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 : 2023-04-03DOI: 10.1080/17509653.2021.2015004
Sina Navidi, Muhammad Motamedi, A. Aghsami, F. Jolai
ABSTRACT The main cause of high-operating costs in open-pit mines is the costs of transportation. Therefore, reducing these costs could have a huge impact on overall mining efficiency and increasing profit. Meanwhile, the high cost of mining equipment, such as shovels and trucks, indicates the necessity of meticulous decision-making to find the optimal shovel-truck combination. In this paper, a new profit function for investing operations in open-pit mines is proposed using queueing theory based on a novel G/M/C//M queueing model. This function tries to maximize profit while considering budget constraints, equipment’s price, and other costs such as occupied servers, idle shovels, service in the queue, and CO2 emission. The proposed model is solved by GAMS software for small-sized instances, and Grasshopper Optimization Algorithm (GOA) is used as a meta-heuristic approach for large-scale problems. Numerical and computational results are provided to prove the efficiency and feasibility of the model. Finally, the presented model is implemented to Chadormalu mine in Iran as a case study.
{"title":"A G/M/C//M queueing model for revenue management of shovel-truck systems in an open-pit mine considering carbon emission, a case study","authors":"Sina Navidi, Muhammad Motamedi, A. Aghsami, F. Jolai","doi":"10.1080/17509653.2021.2015004","DOIUrl":"https://doi.org/10.1080/17509653.2021.2015004","url":null,"abstract":"ABSTRACT The main cause of high-operating costs in open-pit mines is the costs of transportation. Therefore, reducing these costs could have a huge impact on overall mining efficiency and increasing profit. Meanwhile, the high cost of mining equipment, such as shovels and trucks, indicates the necessity of meticulous decision-making to find the optimal shovel-truck combination. In this paper, a new profit function for investing operations in open-pit mines is proposed using queueing theory based on a novel G/M/C//M queueing model. This function tries to maximize profit while considering budget constraints, equipment’s price, and other costs such as occupied servers, idle shovels, service in the queue, and CO2 emission. The proposed model is solved by GAMS software for small-sized instances, and Grasshopper Optimization Algorithm (GOA) is used as a meta-heuristic approach for large-scale problems. Numerical and computational results are provided to prove the efficiency and feasibility of the model. Finally, the presented model is implemented to Chadormalu mine in Iran as a case study.","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41255861","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 : 2023-03-13DOI: 10.1080/17509653.2021.1983737
Saeed Abdolhosseini, Mahsa Ghandehari, A. Ansari, Omid Roozmand
ABSTRACT One of the most important tools is an appropriate pricing mechanism to attract more customers and increase profits. The retailers’ main question is how to set the prices and inventory policies to maximize profit in a competitive heterogeneous market in presence of non-zero lead time and lost sales. A reinforcement learning algorithm is proposed to create appropriate decision-making mechanisms for pricing. A coordinated inventory policy in a competitive environment reduces logistic costs and leads to a higher profit. We use a reinforcement learning algorithm to investigate the performance of a retailer in a competitive environment. An agent-based modeling experimental environment combined with a simulation-optimization method in which a virtual market has been reproduced is used. The market is not homogeneous with respect to customer behavior. It is assumed that the retailer uses (R, Q) policy where the lead time is a fixed amount (L), and the shortage is permissible. The quality, distance, service level, and price are factors that influence customers’ choices. The simulation results for some randomly generated examples show that the algorithm in the competitive environment can make more profit than other available methods and the combined utilization of simulation-optimization methods has been able to find better solutions for the hybrid model of pricing and inventory management considering customer behavior. The results of simulation for three different categories of customers (more sensitive to price, equally sensitive to price, quality and service level, and more sensitive to quality (indicate that the average profit for the proposed algorithm is higher than that of other examined algorithms.
{"title":"Joint pricing and inventory management in a competitive market using reinforcement learning: a combination of the agent-based and simulation-optimization approaches","authors":"Saeed Abdolhosseini, Mahsa Ghandehari, A. Ansari, Omid Roozmand","doi":"10.1080/17509653.2021.1983737","DOIUrl":"https://doi.org/10.1080/17509653.2021.1983737","url":null,"abstract":"ABSTRACT One of the most important tools is an appropriate pricing mechanism to attract more customers and increase profits. The retailers’ main question is how to set the prices and inventory policies to maximize profit in a competitive heterogeneous market in presence of non-zero lead time and lost sales. A reinforcement learning algorithm is proposed to create appropriate decision-making mechanisms for pricing. A coordinated inventory policy in a competitive environment reduces logistic costs and leads to a higher profit. We use a reinforcement learning algorithm to investigate the performance of a retailer in a competitive environment. An agent-based modeling experimental environment combined with a simulation-optimization method in which a virtual market has been reproduced is used. The market is not homogeneous with respect to customer behavior. It is assumed that the retailer uses (R, Q) policy where the lead time is a fixed amount (L), and the shortage is permissible. The quality, distance, service level, and price are factors that influence customers’ choices. The simulation results for some randomly generated examples show that the algorithm in the competitive environment can make more profit than other available methods and the combined utilization of simulation-optimization methods has been able to find better solutions for the hybrid model of pricing and inventory management considering customer behavior. The results of simulation for three different categories of customers (more sensitive to price, equally sensitive to price, quality and service level, and more sensitive to quality (indicate that the average profit for the proposed algorithm is higher than that of other examined algorithms.","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60059187","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 : 2023-03-05DOI: 10.1080/17509653.2023.2183280
L. Ghannam, M. Othman
{"title":"Development of human resource scheduling model in the healthcare sector during the pandemic","authors":"L. Ghannam, M. Othman","doi":"10.1080/17509653.2023.2183280","DOIUrl":"https://doi.org/10.1080/17509653.2023.2183280","url":null,"abstract":"","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44859243","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 : 2023-02-23DOI: 10.1080/17509653.2023.2183278
Ching-Chin Chern, Chun-Ying Leng, Bo Hsiao
{"title":"A heuristic master planning algorithm that includes fairness and flexibility","authors":"Ching-Chin Chern, Chun-Ying Leng, Bo Hsiao","doi":"10.1080/17509653.2023.2183278","DOIUrl":"https://doi.org/10.1080/17509653.2023.2183278","url":null,"abstract":"","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45814888","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 : 2023-02-22DOI: 10.1080/17509653.2023.2183279
F. Zukhruf, Taufiq Suryo Nugroho, Russ Bona Frazila, R. Ramadhan, Alma Rizka Octaviana
{"title":"Evaluating stakeholder structure and private actor involvement on the distribution of relief goods considering a partly centralised decision","authors":"F. Zukhruf, Taufiq Suryo Nugroho, Russ Bona Frazila, R. Ramadhan, Alma Rizka Octaviana","doi":"10.1080/17509653.2023.2183279","DOIUrl":"https://doi.org/10.1080/17509653.2023.2183279","url":null,"abstract":"","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42504126","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 : 2023-02-22DOI: 10.1080/17509653.2023.2174200
L. Varela, G. Putnik, F. Romero
{"title":"Collaborative manufacturing and management contextualization in the Industry 4.0 based on a systematic literature review","authors":"L. Varela, G. Putnik, F. Romero","doi":"10.1080/17509653.2023.2174200","DOIUrl":"https://doi.org/10.1080/17509653.2023.2174200","url":null,"abstract":"","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49046612","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 : 2023-02-19DOI: 10.1080/17509653.2023.2177760
Adnan Sarwar, M. A. Hamza, Saqib Shahzad
ABSTRACT To be competitive, organizations are aiming to achieve operational and environmental performance through the combined adoption of lean and green practices. The literature indicates the positive impact of both paradigms on a firm overall performance. In this study, an analytical network process method and lean-green index were proposed to investigate the impact of lean-green practices on organization performance. The environmental management system is identified as the most significant green practice, while 5S is the most important lean practice. Visual management systems and standard minute value are the most critical practices of leanness. The dynamic sensitivity analysis was performed to check the robustness of the results. The findings might be useful for industrial practitioners and policymakers to strengthen the organization through the assessment and implementation of lean-green practices.
{"title":"Lean –Green Practices and Firm Performance Assessment: An ANP Method","authors":"Adnan Sarwar, M. A. Hamza, Saqib Shahzad","doi":"10.1080/17509653.2023.2177760","DOIUrl":"https://doi.org/10.1080/17509653.2023.2177760","url":null,"abstract":"ABSTRACT To be competitive, organizations are aiming to achieve operational and environmental performance through the combined adoption of lean and green practices. The literature indicates the positive impact of both paradigms on a firm overall performance. In this study, an analytical network process method and lean-green index were proposed to investigate the impact of lean-green practices on organization performance. The environmental management system is identified as the most significant green practice, while 5S is the most important lean practice. Visual management systems and standard minute value are the most critical practices of leanness. The dynamic sensitivity analysis was performed to check the robustness of the results. The findings might be useful for industrial practitioners and policymakers to strengthen the organization through the assessment and implementation of lean-green practices.","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42126602","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 : 2023-02-12DOI: 10.1080/17509653.2023.2174199
Ching-Chin Chern, Wei-Yun Chen, Bo Hsiao
{"title":"A time series analysis approach to forecast price fluctuation points","authors":"Ching-Chin Chern, Wei-Yun Chen, Bo Hsiao","doi":"10.1080/17509653.2023.2174199","DOIUrl":"https://doi.org/10.1080/17509653.2023.2174199","url":null,"abstract":"","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42572892","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 : 2023-02-07DOI: 10.1080/17509653.2023.2174201
Meiling Zhou
{"title":"The effects of sensory interaction and sensory conflict on consumer online review rating behavior","authors":"Meiling Zhou","doi":"10.1080/17509653.2023.2174201","DOIUrl":"https://doi.org/10.1080/17509653.2023.2174201","url":null,"abstract":"","PeriodicalId":46578,"journal":{"name":"International Journal of Management Science and Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45304169","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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