Pub Date : 2021-09-23DOI: 10.1080/03155986.2021.1971432
L. Wu, Qiang Guo, Fuchang Li
Abstract As global environmental problems worsen, issues related to the closed-loop supply chain and trade-in program have gained wide attention. We construct a dual-market model to explore trade-in program and remanufacturing strategies under two scenarios: original equipment manufacturer (OEM) recycling and retailer recycling. We find that under single market strategies, OEM recycling consumers benefit more with the reduction of new product costs. Interestingly, the opposite is true under dual-market strategies with an increase in consumers' maximum willingness to pay in the secondary market. Optimal choices regarding trade-in program strategies and remanufacturing strategies depend on different value ranges of consumers’ maximum willingness to pay in the secondary market, and the cost of the new product.
{"title":"Optimal pricing and trade-in remanufacturing policies considering the secondary market","authors":"L. Wu, Qiang Guo, Fuchang Li","doi":"10.1080/03155986.2021.1971432","DOIUrl":"https://doi.org/10.1080/03155986.2021.1971432","url":null,"abstract":"Abstract As global environmental problems worsen, issues related to the closed-loop supply chain and trade-in program have gained wide attention. We construct a dual-market model to explore trade-in program and remanufacturing strategies under two scenarios: original equipment manufacturer (OEM) recycling and retailer recycling. We find that under single market strategies, OEM recycling consumers benefit more with the reduction of new product costs. Interestingly, the opposite is true under dual-market strategies with an increase in consumers' maximum willingness to pay in the secondary market. Optimal choices regarding trade-in program strategies and remanufacturing strategies depend on different value ranges of consumers’ maximum willingness to pay in the secondary market, and the cost of the new product.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"124 3 1","pages":"547 - 571"},"PeriodicalIF":1.3,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80479724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-11DOI: 10.1080/03155986.2021.1973785
R. Jaballah, Marjolein Veenstra, Leandro C. Coelho, J. Renaud
Abstract We introduce the time-dependent shortest path and vehicle routing problem. In this problem, a set of homogeneous vehicles is used to visit a set of customer locations dispersed over a very large network where the travel times are time-dependent and therefore the shortest path between two locations may change over time. The aim of the problem is to simultaneously determine the sequence in which the customer locations are visited and the arcs traveled on the paths between each pair of consecutively visited customers, such that the total travel time is minimized. We are the first to formally define and solve this fully integrated problem, providing tight bounds to it. We then propose a dynamic time-dependent shortest path algorithm embedded within a simulated annealing metaheuristic to efficiently solve the problem. We also propose a variant of the algorithm where some time-dependent shortest paths are precomputed. We test our formulations and algorithms on a set of real-life instances generated from a dataset of the road network in Québec City, Canada. Our results indicate that the resulting models are too large to be solved even for small instances. However, the obtained bounds show that the developed simulated annealing heuristic performs very well. We also demonstrate that neglecting time-dependent information on traffic leads to imprecise estimation of the traveling time. Moreover, the results show the importance of solving the shortest paths and routing problems simultaneously, as using a set of precomputed shortest paths leads to slightly worse solutions. This work adds new research avenues to city logistics and congestion studies.
{"title":"The time-dependent shortest path and vehicle routing problem","authors":"R. Jaballah, Marjolein Veenstra, Leandro C. Coelho, J. Renaud","doi":"10.1080/03155986.2021.1973785","DOIUrl":"https://doi.org/10.1080/03155986.2021.1973785","url":null,"abstract":"Abstract We introduce the time-dependent shortest path and vehicle routing problem. In this problem, a set of homogeneous vehicles is used to visit a set of customer locations dispersed over a very large network where the travel times are time-dependent and therefore the shortest path between two locations may change over time. The aim of the problem is to simultaneously determine the sequence in which the customer locations are visited and the arcs traveled on the paths between each pair of consecutively visited customers, such that the total travel time is minimized. We are the first to formally define and solve this fully integrated problem, providing tight bounds to it. We then propose a dynamic time-dependent shortest path algorithm embedded within a simulated annealing metaheuristic to efficiently solve the problem. We also propose a variant of the algorithm where some time-dependent shortest paths are precomputed. We test our formulations and algorithms on a set of real-life instances generated from a dataset of the road network in Québec City, Canada. Our results indicate that the resulting models are too large to be solved even for small instances. However, the obtained bounds show that the developed simulated annealing heuristic performs very well. We also demonstrate that neglecting time-dependent information on traffic leads to imprecise estimation of the traveling time. Moreover, the results show the importance of solving the shortest paths and routing problems simultaneously, as using a set of precomputed shortest paths leads to slightly worse solutions. This work adds new research avenues to city logistics and congestion studies.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"133 1","pages":"592 - 622"},"PeriodicalIF":1.3,"publicationDate":"2021-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84074954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-02DOI: 10.1080/03155986.2021.1914963
F. Sarrazin, L. Lebel, N. Lehoux
Abstract The recent difficulties of the wood industry in Canada (decline of the pulp and paper sector, decline in available fiber volume, 2008–2009 housing crisis, etc.) and mounting pressures for a more efficient use of natural resources make it all the more relevant to examine how to make better use of the forest resource. In this regard, the creation of sorting and consolidation yards, distinct from forest sites and mills, offers multiple opportunities for value maximization and cost minimization. This article aims to better understand the interaction between a forest logistics center and a complex forest network while exploring several geo-economic factors favoring the use of such a structure. A profit maximization model is proposed and applied for a case study in the Mauricie region of Quebec, Canada. The results showed that a logistics center would increase the profit by $0.90 (Canadian dollars) for each cubic meter of wood available for harvesting, notably through an increase in the volume of wood processed into finished products of up to 83,000 m3 annually (or 4.6%). A dynamic effect of up to 17% was also observed between the operation of a processing yard and the use of load returns.
{"title":"Regional logistics centre: Application to Eastern Canada","authors":"F. Sarrazin, L. Lebel, N. Lehoux","doi":"10.1080/03155986.2021.1914963","DOIUrl":"https://doi.org/10.1080/03155986.2021.1914963","url":null,"abstract":"Abstract The recent difficulties of the wood industry in Canada (decline of the pulp and paper sector, decline in available fiber volume, 2008–2009 housing crisis, etc.) and mounting pressures for a more efficient use of natural resources make it all the more relevant to examine how to make better use of the forest resource. In this regard, the creation of sorting and consolidation yards, distinct from forest sites and mills, offers multiple opportunities for value maximization and cost minimization. This article aims to better understand the interaction between a forest logistics center and a complex forest network while exploring several geo-economic factors favoring the use of such a structure. A profit maximization model is proposed and applied for a case study in the Mauricie region of Quebec, Canada. The results showed that a logistics center would increase the profit by $0.90 (Canadian dollars) for each cubic meter of wood available for harvesting, notably through an increase in the volume of wood processed into finished products of up to 83,000 m3 annually (or 4.6%). A dynamic effect of up to 17% was also observed between the operation of a processing yard and the use of load returns.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"34 1","pages":"439 - 464"},"PeriodicalIF":1.3,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89078155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-02DOI: 10.1080/03155986.2021.1923978
A. Saif, Ali Keyvandarian, S. Elhedhli
Abstract This article presents an extended facility location model for multiproduct supply chain network design, that accounts for concave capacity, transportation, and inventory costs (induced by economies of scale, quantity discounts and risk pooling, respectively). The problem is formulated as a mixed-integer nonlinear program (MINLP) with linear constraints and a large number of separable concave terms in the objective function. We propose a solution approach that combines stabilized Lagrangian relaxation with a novel Benders decomposition. Lagrangian relaxation is used first to decompose the problem by potential warehouse location into low-rank concave minimization subproblems. Benders decomposition is then applied to solve the subproblems by shifting the concave terms to a low-dimensional master problem that is solved effectively through implicit enumeration. Finally, a feasible solution for the original problem is constructed from the partial subproblems solutions by solving a restricted set covering problem. The proposed approach is tested on several instances from the literature and compared against a state-of-the-art solver. Furthermore, a realistic case study is used to demonstrate the impact of concavities in the cost components with extensive sensitivity analyses.
{"title":"A new Lagrangian-Benders approach for a concave cost supply chain network design problem","authors":"A. Saif, Ali Keyvandarian, S. Elhedhli","doi":"10.1080/03155986.2021.1923978","DOIUrl":"https://doi.org/10.1080/03155986.2021.1923978","url":null,"abstract":"Abstract This article presents an extended facility location model for multiproduct supply chain network design, that accounts for concave capacity, transportation, and inventory costs (induced by economies of scale, quantity discounts and risk pooling, respectively). The problem is formulated as a mixed-integer nonlinear program (MINLP) with linear constraints and a large number of separable concave terms in the objective function. We propose a solution approach that combines stabilized Lagrangian relaxation with a novel Benders decomposition. Lagrangian relaxation is used first to decompose the problem by potential warehouse location into low-rank concave minimization subproblems. Benders decomposition is then applied to solve the subproblems by shifting the concave terms to a low-dimensional master problem that is solved effectively through implicit enumeration. Finally, a feasible solution for the original problem is constructed from the partial subproblems solutions by solving a restricted set covering problem. The proposed approach is tested on several instances from the literature and compared against a state-of-the-art solver. Furthermore, a realistic case study is used to demonstrate the impact of concavities in the cost components with extensive sensitivity analyses.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"74 1","pages":"495 - 516"},"PeriodicalIF":1.3,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80743450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-30DOI: 10.1080/03155986.2021.1939841
Qin Zhou, Kum Fai Yuen
Abstract Traditional behavior-based pricing (BBP) literature suggests that firms should offer lower prices to incentivize new customers to switch. However, at the time of switch, customers are often uncertain about their true needs or valuations of the product. Accordingly, they may experience repeat-purchase or switch-purchase regret, depending on whether they have bought a product from the same brand or switched to another brand. This paper investigates the impact of customers’ anticipated regret on firms’ BBP strategy and profits. Contrary to prior research which generally shows that firms performing BBP yield lower profits, we find that firms’ profits can increase or decrease in the presence of anticipated regret. When customers’ anticipated regret is sufficiently strong, firms can benefit from performing BBP. In addition, we find that firms have to change their traditional BBP strategy from rewarding new customers to rewarding repeat customers when repeat-purchase regret is sufficiently high.
{"title":"Behavior-based pricing: an analysis of the impact of anticipated regret","authors":"Qin Zhou, Kum Fai Yuen","doi":"10.1080/03155986.2021.1939841","DOIUrl":"https://doi.org/10.1080/03155986.2021.1939841","url":null,"abstract":"Abstract Traditional behavior-based pricing (BBP) literature suggests that firms should offer lower prices to incentivize new customers to switch. However, at the time of switch, customers are often uncertain about their true needs or valuations of the product. Accordingly, they may experience repeat-purchase or switch-purchase regret, depending on whether they have bought a product from the same brand or switched to another brand. This paper investigates the impact of customers’ anticipated regret on firms’ BBP strategy and profits. Contrary to prior research which generally shows that firms performing BBP yield lower profits, we find that firms’ profits can increase or decrease in the presence of anticipated regret. When customers’ anticipated regret is sufficiently strong, firms can benefit from performing BBP. In addition, we find that firms have to change their traditional BBP strategy from rewarding new customers to rewarding repeat customers when repeat-purchase regret is sufficiently high.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"84 1","pages":"517 - 546"},"PeriodicalIF":1.3,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81136201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-19DOI: 10.1080/03155986.2021.1918487
Lita Das, Andre L. Carrel, C. Caplice
Abstract Due to constraints on pack sizes in which products are shipped to retail stores, excess inventory can accumulate in stores. In order to optimize the allocation of store space between storage and customer-facing areas, simple expressions are required for backroom inventory levels that can be inserted into optimization models. This paper systematically investigates the effect of pack size constraints on in-store inventory and storage space needs. The context and problem definition are based on a limited service restaurant setting. An approximation for the distribution of inventory positions after replenishment is proposed, and its accuracy is compared to results obtained from simulation. Furthermore, the effect of pack size constraints on the probability of stock-outs is derived. The expressions are found to be good approximations that are usable in complex optimization models for store space allocation. Building on these results, we perform exploratory analyses and demonstrate how increasing pack sizes increases service levels but also removes revenue-generating frontroom space because by increasing backroom space requirements.
{"title":"Pack size effects on retail store inventory and storage space needs","authors":"Lita Das, Andre L. Carrel, C. Caplice","doi":"10.1080/03155986.2021.1918487","DOIUrl":"https://doi.org/10.1080/03155986.2021.1918487","url":null,"abstract":"Abstract Due to constraints on pack sizes in which products are shipped to retail stores, excess inventory can accumulate in stores. In order to optimize the allocation of store space between storage and customer-facing areas, simple expressions are required for backroom inventory levels that can be inserted into optimization models. This paper systematically investigates the effect of pack size constraints on in-store inventory and storage space needs. The context and problem definition are based on a limited service restaurant setting. An approximation for the distribution of inventory positions after replenishment is proposed, and its accuracy is compared to results obtained from simulation. Furthermore, the effect of pack size constraints on the probability of stock-outs is derived. The expressions are found to be good approximations that are usable in complex optimization models for store space allocation. Building on these results, we perform exploratory analyses and demonstrate how increasing pack sizes increases service levels but also removes revenue-generating frontroom space because by increasing backroom space requirements.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"11 1","pages":"465 - 494"},"PeriodicalIF":1.3,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88684600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-19DOI: 10.1080/03155986.2021.1907872
Yauheni Kisialiou, Irina Gribkovskaia, G. Laporte
Abstract We solve a periodic supply vessel planning problem under demand and weather uncertainty, arising in offshore of oil and gas production. Our study is motivated by the case of the Norwegian energy operator Equinor which supplied us with data. The aim is to determine an optimal fleet composition and a least-cost vessel schedule under uncertain demand at the installations and uncertain weather conditions. We present a methodology incorporating a metaheuristic within a discrete-event simulation model which, applied iteratively for the increasing values of reliability level parameters, yields a vessel schedule of least expected cost.
{"title":"Periodic supply vessel planning under demand and weather uncertainty","authors":"Yauheni Kisialiou, Irina Gribkovskaia, G. Laporte","doi":"10.1080/03155986.2021.1907872","DOIUrl":"https://doi.org/10.1080/03155986.2021.1907872","url":null,"abstract":"Abstract We solve a periodic supply vessel planning problem under demand and weather uncertainty, arising in offshore of oil and gas production. Our study is motivated by the case of the Norwegian energy operator Equinor which supplied us with data. The aim is to determine an optimal fleet composition and a least-cost vessel schedule under uncertain demand at the installations and uncertain weather conditions. We present a methodology incorporating a metaheuristic within a discrete-event simulation model which, applied iteratively for the increasing values of reliability level parameters, yields a vessel schedule of least expected cost.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"84 1","pages":"411 - 438"},"PeriodicalIF":1.3,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83828878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-03DOI: 10.1080/03155986.2021.1905418
R. Guillaume, O. Ammar, C. Thierry
Abstract In this paper, we consider the problem of allocation of Emergency Vehicles (EVs) to Rescue Centers (RCs). The objective is to improve the operational response of the Fire and Rescue Services (SDIS) in France. More precisely, we focus on the mid-term management, and on the process of redeployment of EVs in RCs according to the evolution of requirements. At this level of decision, we do not have information on accidents. We only used the available information on the simultaneity of requirements. Based on the Hurwicz criterion, we develop a mathematical model and an iterative algorithm to solve it. The proposed approach takes into account both the uncertainty on the occurrence sequence of accidents, and the attitude towards optimization of the decision maker (DM). An illustration from the DM’s point of view is presented. It shows that this uncertainty significantly impacts the deployment of EVs. Results show that the proposed approach has an efficient resolution time for real size problems.
{"title":"Mid-term redeployment of capacity of rescue centers considering the optimism of the decision maker","authors":"R. Guillaume, O. Ammar, C. Thierry","doi":"10.1080/03155986.2021.1905418","DOIUrl":"https://doi.org/10.1080/03155986.2021.1905418","url":null,"abstract":"Abstract In this paper, we consider the problem of allocation of Emergency Vehicles (EVs) to Rescue Centers (RCs). The objective is to improve the operational response of the Fire and Rescue Services (SDIS) in France. More precisely, we focus on the mid-term management, and on the process of redeployment of EVs in RCs according to the evolution of requirements. At this level of decision, we do not have information on accidents. We only used the available information on the simultaneity of requirements. Based on the Hurwicz criterion, we develop a mathematical model and an iterative algorithm to solve it. The proposed approach takes into account both the uncertainty on the occurrence sequence of accidents, and the attitude towards optimization of the decision maker (DM). An illustration from the DM’s point of view is presented. It shows that this uncertainty significantly impacts the deployment of EVs. Results show that the proposed approach has an efficient resolution time for real size problems.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"9 1","pages":"333 - 352"},"PeriodicalIF":1.3,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78276317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-06DOI: 10.1080/03155986.2021.1907073
C. Larsen
Abstract The paper analyzes a multi-item inventory system, using independent (R,Q) policies. The aim is to minimize the average stock level while keeping a weighted (across items) fill rate service level at a given target. The paper explores whether the optimal order sizes and the optimal safety factors are aligned with the ABC classification. Our results show that A items should be ordered more frequently followed by B items and C items. Concerning the optimal safety factors, our results depend on the weights applied in the specification of the weighted service level. If all items have equal weight, A items should have the lowest safety factors followed by B and C items. If the weights are the demand rates, the ranking of the safety factors follows the ratios between the demand rate and the unit purchase price, and the higher this ratio is, the higher is the optimal safety factor. However, this ranking is completely aligned with the ABC classification given that the demands are transformed into monetary units.
{"title":"Alignment between an ABC classification and results from an optimization approach","authors":"C. Larsen","doi":"10.1080/03155986.2021.1907073","DOIUrl":"https://doi.org/10.1080/03155986.2021.1907073","url":null,"abstract":"Abstract The paper analyzes a multi-item inventory system, using independent (R,Q) policies. The aim is to minimize the average stock level while keeping a weighted (across items) fill rate service level at a given target. The paper explores whether the optimal order sizes and the optimal safety factors are aligned with the ABC classification. Our results show that A items should be ordered more frequently followed by B items and C items. Concerning the optimal safety factors, our results depend on the weights applied in the specification of the weighted service level. If all items have equal weight, A items should have the lowest safety factors followed by B and C items. If the weights are the demand rates, the ranking of the safety factors follows the ratios between the demand rate and the unit purchase price, and the higher this ratio is, the higher is the optimal safety factor. However, this ranking is completely aligned with the ABC classification given that the demands are transformed into monetary units.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"34 1","pages":"400 - 410"},"PeriodicalIF":1.3,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78003410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-02DOI: 10.1080/03155986.2021.1904538
Settar Mustu, T. Eren
Abstract This paper concerns with the total weighted tardiness on a single machine scheduling problem with the concept of learning effect and unequal release dates. A mathematical model is proposed with binary variables and only small size problems can be solved efficiently due to its NP-hardness. Therefore, four heuristic methods are developed to solve real size applications including the size of 1000 jobs. Proposed heuristics are: genetic, genetic with solution combination, kangaroo and genetic-kangaroo hybrid algorithms. Results denote that developed heuristics are efficient for the considered problem. Research on this topic shows that no study exists on the total weighted tardiness problem with learning effect and unequal release dates simultaneously tackled in this paper.
{"title":"Minimization of the total weighted tardiness on a single machine scheduling problem with a position based learning effect and unequal release dates","authors":"Settar Mustu, T. Eren","doi":"10.1080/03155986.2021.1904538","DOIUrl":"https://doi.org/10.1080/03155986.2021.1904538","url":null,"abstract":"Abstract This paper concerns with the total weighted tardiness on a single machine scheduling problem with the concept of learning effect and unequal release dates. A mathematical model is proposed with binary variables and only small size problems can be solved efficiently due to its NP-hardness. Therefore, four heuristic methods are developed to solve real size applications including the size of 1000 jobs. Proposed heuristics are: genetic, genetic with solution combination, kangaroo and genetic-kangaroo hybrid algorithms. Results denote that developed heuristics are efficient for the considered problem. Research on this topic shows that no study exists on the total weighted tardiness problem with learning effect and unequal release dates simultaneously tackled in this paper.","PeriodicalId":13645,"journal":{"name":"Infor","volume":"6 1","pages":"353 - 376"},"PeriodicalIF":1.3,"publicationDate":"2021-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78578757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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