The presented paper considers the pricing and lot-sizing decisions for a manufacturer who produces and sells a single product in different selling channels i.e physical stock, website, mobile, etc. The objective is to find the production plan and prices of each channel to maximize the total profit defined from difference between the revenues and the productions, holding and setups costs. The consumers’ demand in each channel is represented by attraction demand models which include the multinomial logit (), multiplicative competitive interaction () and linear demand models. The addressed problem is formulated as a non-convex mixed-integer nonlinear program (). Based on properties of attraction functions, an efficient reformulation which transforms the initial non-convex problem into a convex one is presented. Therefore, an optimization approach based on the outer approximation algorithm is presented to solve the problem. Numerical tests based on large benchmark of real inspired instances show the efficiency of the proposed approach to solve the addressed problem compared to the initial non-convex model.
{"title":"Lot-sizing and pricing decisions under attraction demand models and multi-channel environment: New efficient formulations","authors":"Mourad Terzi , Yassine Ouazene , Alice Yalaoui , Farouk Yalaoui","doi":"10.1016/j.orp.2023.100269","DOIUrl":"10.1016/j.orp.2023.100269","url":null,"abstract":"<div><p>The presented paper considers the pricing and lot-sizing decisions for a manufacturer who produces and sells a single product in different selling channels i.e physical stock, website, mobile, etc. The objective is to find the production plan and prices of each channel to maximize the total profit defined from difference between the revenues and the productions, holding and setups costs. The consumers’ demand in each channel is represented by attraction demand models which include the multinomial logit (<span><math><mrow><mi>M</mi><mi>N</mi><mi>L</mi></mrow></math></span>), multiplicative competitive interaction (<span><math><mrow><mi>M</mi><mi>C</mi><mi>I</mi></mrow></math></span>) and linear demand models. The addressed problem is formulated as a non-convex mixed-integer nonlinear program (<span><math><mrow><mi>M</mi><mi>I</mi><mi>N</mi><mi>L</mi><mi>P</mi></mrow></math></span>). Based on properties of attraction functions, an efficient reformulation which transforms the initial non-convex problem into a convex one is presented. Therefore, an optimization approach based on the outer approximation algorithm is presented to solve the problem. Numerical tests based on large benchmark of real inspired instances show the efficiency of the proposed approach to solve the addressed problem compared to the initial non-convex model.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"10 ","pages":"Article 100269"},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48138965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1016/j.orp.2022.100263
Shafi Ahmad , Sarfaraz Masood , Noor Zaman Khan , Irfan Anjum Badruddin , Ompal , Ali Ahmadian , Zahid A. Khan , Amil Hayat Khan
Recently, a large portion of the world's population has experienced an unprecedented devastating effect of the COVID-19 pandemic. At the time of its outbreak, not much was known about this disease and therefore, quarantine and social distancing were the only ways suggested to prevent its spread among humans. Although the current situation is much better than before however, strict social distancing norms as well as frequent long-lasting lockdowns with stringent guidelines and actions to control the spread in the early days have affected the physical and psychological health of the people. Consequently, this study was carried out to attain the following major objectives: (i) to identify the potential psychological problems/factors that might have been caused due to COVID-19 led social distancing and lockdowns, and (ii) to determine the ranks of the identified psychological factors to reflect their degree of criticality. The first objective was achieved by gathering information about the potential psychological factors from the experts. Data, in terms of linguistic variables, was collected from the experts and analyzed using two fuzzy-based multi-criteria decision-making (MCDM) methods i.e. Fuzzy Best Worst Method (F-BWM) and Fuzzy TOPSIS (F-TOPSIS) which led to the accomplishment of the second objective. The results of this study revealed that anxiety, stress, panic attacks, frustration, and insomnia were the top five critical psychological factors that might have affected people due to this pandemic. Consistency of the results was ensured by comparing the obtained ranks with the ranks found using the Fuzzy WSM and Fuzzy MABAC methods. In addition, the robustness of the results was ascertained by conducting the sensitivity analysis. Based on the findings of the study, the identified factors were categorized into most, average, and least critical psychological factors. This research might help the relevant authorities to understand the extent of the seriousness of the various psychological factors caused by this pandemic, so that an effective strategy may be developed for better management, control, and safety.
{"title":"Analysing the impact of COVID-19 pandemic on the psychological health of people using fuzzy MCDM methods","authors":"Shafi Ahmad , Sarfaraz Masood , Noor Zaman Khan , Irfan Anjum Badruddin , Ompal , Ali Ahmadian , Zahid A. Khan , Amil Hayat Khan","doi":"10.1016/j.orp.2022.100263","DOIUrl":"10.1016/j.orp.2022.100263","url":null,"abstract":"<div><p>Recently, a large portion of the world's population has experienced an unprecedented devastating effect of the COVID-19 pandemic. At the time of its outbreak, not much was known about this disease and therefore, quarantine and social distancing were the only ways suggested to prevent its spread among humans. Although the current situation is much better than before however, strict social distancing norms as well as frequent long-lasting lockdowns with stringent guidelines and actions to control the spread in the early days have affected the physical and psychological health of the people. Consequently, this study was carried out to attain the following major objectives: (i) to identify the potential psychological problems/factors that might have been caused due to COVID-19 led social distancing and lockdowns, and (ii) to determine the ranks of the identified psychological factors to reflect their degree of criticality. The first objective was achieved by gathering information about the potential psychological factors from the experts. Data, in terms of linguistic variables, was collected from the experts and analyzed using two fuzzy-based multi-criteria decision-making (MCDM) methods i.e. Fuzzy Best Worst Method (F-BWM) and Fuzzy TOPSIS (F-TOPSIS) which led to the accomplishment of the second objective. The results of this study revealed that anxiety, stress, panic attacks, frustration, and insomnia were the top five critical psychological factors that might have affected people due to this pandemic. Consistency of the results was ensured by comparing the obtained ranks with the ranks found using the Fuzzy WSM and Fuzzy MABAC methods. In addition, the robustness of the results was ascertained by conducting the sensitivity analysis. Based on the findings of the study, the identified factors were categorized into most, average, and least critical psychological factors. This research might help the relevant authorities to understand the extent of the seriousness of the various psychological factors caused by this pandemic, so that an effective strategy may be developed for better management, control, and safety.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"10 ","pages":"Article 100263"},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45982412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1016/j.orp.2023.100268
J.M. Morales, M.A. Muñoz, S. Pineda
We consider a two-stage generation scheduling problem comprising a forward dispatch and a real-time re-dispatch. The former must be conducted facing an uncertain net demand that includes non-dispatchable electricity consumption and renewable power generation. The latter copes with the plausible deviations with respect to the forward schedule by making use of balancing power during the actual operation of the system. Standard industry practice deals with the uncertain net demand in the forward stage by replacing it with a good estimate of its conditional expectation (usually referred to as a point forecast), so as to minimize the need for balancing power in real time. However, it is well known that the cost structure of a power system is highly asymmetric and dependent on its operating point, with the result that minimizing the amount of power imbalances is not necessarily aligned with minimizing operating costs. In this paper, we propose a bilevel program to construct, from the available historical data, a prescription of the net demand that does account for the power system’s cost asymmetry. Furthermore, to accommodate the strong dependence of this cost on the power system’s operating point, we use clustering to tailor the proposed prescription to the foreseen net-demand regime. By way of an illustrative example and a more realistic case study based on the European power system, we show that our approach leads to substantial cost savings compared to the customary way of doing.
{"title":"Prescribing net demand for two-stage electricity generation scheduling","authors":"J.M. Morales, M.A. Muñoz, S. Pineda","doi":"10.1016/j.orp.2023.100268","DOIUrl":"https://doi.org/10.1016/j.orp.2023.100268","url":null,"abstract":"<div><p>We consider a two-stage generation scheduling problem comprising a forward dispatch and a real-time re-dispatch. The former must be conducted facing an uncertain net demand that includes non-dispatchable electricity consumption and renewable power generation. The latter copes with the plausible deviations with respect to the forward schedule by making use of balancing power during the actual operation of the system. Standard industry practice deals with the uncertain net demand in the forward stage by replacing it with a good estimate of its conditional expectation (usually referred to as a <em>point forecast</em>), so as to minimize the need for balancing power in real time. However, it is well known that the cost structure of a power system is highly asymmetric and dependent on its operating point, with the result that minimizing the amount of power imbalances is not necessarily aligned with minimizing operating costs. In this paper, we propose a bilevel program to construct, from the available historical data, a <em>prescription</em> of the net demand that does account for the power system’s cost asymmetry. Furthermore, to accommodate the strong dependence of this cost on the power system’s operating point, we use clustering to tailor the proposed prescription to the foreseen net-demand regime. By way of an illustrative example and a more realistic case study based on the European power system, we show that our approach leads to substantial cost savings compared to the customary way of doing.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"10 ","pages":"Article 100268"},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49869947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1016/j.orp.2023.100266
Wuyang Yu
Proper prepositioning of emergency supplies can dramatically improve the efficiency of emergency response work. However, the uncertainties of emergency demands and road conditions bring difficulties to the prepositioning of emergency supplies. This paper proposes a two-stage robust model to locate emergency supply points and preposition the corresponding storage amount of emergency supplies, in which we presented two budget sets to describe the uncertainties of demands and road conditions, respectively. The innovative use of variables in the model to limit road capacities addresses the representation of different road interruption scenarios. We proposed an algorithm based on Benders decomposition by transforming the second-stage model into a binary linear programming model. Computational experiments based on the Sioux Falls network demonstrate the validity of the model and algorithm. We conducted sensitivity analyses for some important parameters in the model, such as two uncertainty control parameters, unit transportation cost, budget for the construction of emergency supply points, etc. We find that the uncertainty of road disruptions has a greater impact on the model than the uncertainty of demands. In addition, when the control parameter of the road disruptions exceeds a certain threshold, its influence on the model remains essentially constant.
{"title":"A robust model for emergency supplies prepositioning and transportation considering road disruptions","authors":"Wuyang Yu","doi":"10.1016/j.orp.2023.100266","DOIUrl":"https://doi.org/10.1016/j.orp.2023.100266","url":null,"abstract":"<div><p>Proper prepositioning of emergency supplies can dramatically improve the efficiency of emergency response work. However, the uncertainties of emergency demands and road conditions bring difficulties to the prepositioning of emergency supplies. This paper proposes a two-stage robust model to locate emergency supply points and preposition the corresponding storage amount of emergency supplies, in which we presented two budget sets to describe the uncertainties of demands and road conditions, respectively. The innovative use of variables in the model to limit road capacities addresses the representation of different road interruption scenarios. We proposed an algorithm based on Benders decomposition by transforming the second-stage model into a binary linear programming model. Computational experiments based on the Sioux Falls network demonstrate the validity of the model and algorithm. We conducted sensitivity analyses for some important parameters in the model, such as two uncertainty control parameters, unit transportation cost, budget for the construction of emergency supply points, etc. We find that the uncertainty of road disruptions has a greater impact on the model than the uncertainty of demands. In addition, when the control parameter of the road disruptions exceeds a certain threshold, its influence on the model remains essentially constant.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"10 ","pages":"Article 100266"},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49869948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1016/j.orp.2022.100262
Yuichi Takano , Jun-ya Gotoh
This paper is concerned with a linear control policy for dynamic portfolio selection. We develop this policy by incorporating time-series behaviors of asset returns on the basis of coherent risk minimization. Analyzing the dual form of our optimization model, we demonstrate that the investment performance of linear control policies is directly connected to the intertemporal covariance of asset returns. To mitigate overfitting to training data (i.e., historical asset returns), we apply robust optimization. For this optimization, we prove that the worst-case coherent risk measure can be decomposed into the empirical risk measure and the penalty terms. Numerical results demonstrate that when the number of assets is small, linear control policies deliver good out-of-sample investment performance. When the number of assets is large, the penalty terms improve the out-of-sample investment performance.
{"title":"Dynamic portfolio selection with linear control policies for coherent risk minimization","authors":"Yuichi Takano , Jun-ya Gotoh","doi":"10.1016/j.orp.2022.100262","DOIUrl":"10.1016/j.orp.2022.100262","url":null,"abstract":"<div><p>This paper is concerned with a linear control policy for dynamic portfolio selection. We develop this policy by incorporating time-series behaviors of asset returns on the basis of coherent risk minimization. Analyzing the dual form of our optimization model, we demonstrate that the investment performance of linear control policies is directly connected to the intertemporal covariance of asset returns. To mitigate overfitting to training data (i.e., historical asset returns), we apply robust optimization. For this optimization, we prove that the worst-case coherent risk measure can be decomposed into the empirical risk measure and the penalty terms. Numerical results demonstrate that when the number of assets is small, linear control policies deliver good out-of-sample investment performance. When the number of assets is large, the penalty terms improve the out-of-sample investment performance.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"10 ","pages":"Article 100262"},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41346948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1016/j.orp.2023.100274
Yonit Barron
We study a stochastic continuous-review card balance management problem with two transaction patterns, namely, continuous and batch-type bilateral transactions, both in a Markovian environment. Motivated by the Autoload program used in public transit systems, the card is managed using a two-parameter band policy. Our cost structure includes activation and loading costs, and a fine for a negative balance. By applying hitting time theory and martingales, we derive the cost functionals and obtain, numerically, the optimal thresholds minimizing the expected discounted total cost. Surprisingly, a numerical study shows that the optimal policy is inherently linked with the outflow patterns, and is more sensitive to changes in withdrawal rates than to changes in batch sizes. We further show that timing is a significant factor in determining the policy: a high discount factor leads to frequent activations with smaller amounts.
{"title":"A stochastic card balance management problem with continuous and batch-type bilateral transactions","authors":"Yonit Barron","doi":"10.1016/j.orp.2023.100274","DOIUrl":"10.1016/j.orp.2023.100274","url":null,"abstract":"<div><p>We study a stochastic continuous-review card balance management problem with two transaction patterns, namely, continuous and batch-type bilateral transactions, both in a Markovian environment. Motivated by the Autoload program used in public transit systems, the card is managed using a two-parameter band policy. Our cost structure includes activation and loading costs, and a fine for a negative balance. By applying hitting time theory and martingales, we derive the cost functionals and obtain, numerically, the optimal thresholds minimizing the expected discounted total cost. Surprisingly, a numerical study shows that the optimal policy is inherently linked with the outflow patterns, and is more sensitive to changes in withdrawal rates than to changes in batch sizes. We further show that timing is a significant factor in determining the policy: a high discount factor leads to frequent activations with smaller amounts.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"10 ","pages":"Article 100274"},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45293799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1016/j.orp.2022.100265
A. Salimipour, Toktam Mehraban, Hevi Ghafour, N. Arshad, M. J. Ebadi
{"title":"SIR model for the spread of COVID-19: A case study","authors":"A. Salimipour, Toktam Mehraban, Hevi Ghafour, N. Arshad, M. J. Ebadi","doi":"10.1016/j.orp.2022.100265","DOIUrl":"https://doi.org/10.1016/j.orp.2022.100265","url":null,"abstract":"","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"10 1","pages":"100265 - 100265"},"PeriodicalIF":2.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43731707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1016/j.orp.2022.100260
Luis Martínez, María Merino, Juan Manuel Montoya
{"title":"An integer programming model for obtaining cyclic quasi-difference matrices","authors":"Luis Martínez, María Merino, Juan Manuel Montoya","doi":"10.1016/j.orp.2022.100260","DOIUrl":"https://doi.org/10.1016/j.orp.2022.100260","url":null,"abstract":"","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"19 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54965575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1016/j.orp.2022.100245
Mohamed Amjath , Laoucine Kerbache , James MacGregor Smith , Adel Elomri
Material handling systems (MHS) are integral to logistics functions by providing various supports such as handling, moving, and storing materials in manufacturing and service organisations. This study considers determining the optimal size of a homogeneous fleet of trucks to be outsourced (or subcontracted) from a third-party logistics provider to be used daily to cyclically transport different types of raw materials from designated storage yards to intermediate buffer locations to be fed as inputs to a production facility for processing. Within this context, the problem is modelled as a closed queueing network (CQN) combined with mixed-integer nonlinear programming (MINLP) to determine the optimal fleet size. This study proposes an analytical method based on sequential quadratic programming (SQP) methodology coupled with a mean value analysis (MVA) algorithm to solve this NP-Hard problem. Furthermore, a discrete event simulation (DES) model is developed to validate the optimisation of non-dominant solutions. The proposed analytical approach, along with the simulation, are implemented in a real case study of a steel manufacturing setup. Analytical model results are validated using the simulation results, which are proved to be very accurate, with deviations ranges within ±7%.
{"title":"Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks","authors":"Mohamed Amjath , Laoucine Kerbache , James MacGregor Smith , Adel Elomri","doi":"10.1016/j.orp.2022.100245","DOIUrl":"10.1016/j.orp.2022.100245","url":null,"abstract":"<div><p>Material handling systems (MHS) are integral to logistics functions by providing various supports such as handling, moving, and storing materials in manufacturing and service organisations. This study considers determining the optimal size of a homogeneous fleet of trucks to be outsourced (or subcontracted) from a third-party logistics provider to be used daily to cyclically transport different types of raw materials from designated storage yards to intermediate buffer locations to be fed as inputs to a production facility for processing. Within this context, the problem is modelled as a closed queueing network (CQN) combined with mixed-integer nonlinear programming (MINLP) to determine the optimal fleet size. This study proposes an analytical method based on sequential quadratic programming (SQP) methodology coupled with a mean value analysis (MVA) algorithm to solve this NP-Hard problem. Furthermore, a discrete event simulation (DES) model is developed to validate the optimisation of non-dominant solutions. The proposed analytical approach, along with the simulation, are implemented in a real case study of a steel manufacturing setup. Analytical model results are validated using the simulation results, which are proved to be very accurate, with deviations ranges within ±7%.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"9 ","pages":"Article 100245"},"PeriodicalIF":2.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214716022000185/pdfft?md5=87fd4af279af8a71fe389f300b0f2dfa&pid=1-s2.0-S2214716022000185-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49100733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1016/j.orp.2022.100221
Dana Marsetiya Utama , Imam Santoso , Yusuf Hendrawan , Wike Agustin Prima Dania
Inventory affects the production process and supply chain activities. Integrated decision inventory improves performance and optimizes supply chain activities. However, its disadvantage is the Integrated Procurement Production (IPP) inventory model, which manages the raw material inventory in procurement activities, works in process, and finished products. This study reviewed the IPP inventory model problem using a systematic review of 102 published papers from 1992 to 2021. The reviewed papers were based on complexity, type of model, data, time dynamics, optimization, solution, and paper. This study presented the IPP inventory model analysis, gap, and future study directions.
{"title":"Integrated procurement-production inventory model in supply chain: A systematic review","authors":"Dana Marsetiya Utama , Imam Santoso , Yusuf Hendrawan , Wike Agustin Prima Dania","doi":"10.1016/j.orp.2022.100221","DOIUrl":"10.1016/j.orp.2022.100221","url":null,"abstract":"<div><p>Inventory affects the production process and supply chain activities. Integrated decision inventory improves performance and optimizes supply chain activities. However, its disadvantage is the Integrated Procurement Production (IPP) inventory model, which manages the raw material inventory in procurement activities, works in process, and finished products. This study reviewed the IPP inventory model problem using a systematic review of 102 published papers from 1992 to 2021. The reviewed papers were based on complexity, type of model, data, time dynamics, optimization, solution, and paper. This study presented the IPP inventory model analysis, gap, and future study directions.</p></div>","PeriodicalId":38055,"journal":{"name":"Operations Research Perspectives","volume":"9 ","pages":"Article 100221"},"PeriodicalIF":2.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S221471602200001X/pdfft?md5=6ad2ffdfa0684d656f839f85098e3013&pid=1-s2.0-S221471602200001X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44641141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}