Pub Date : 2023-10-28DOI: 10.1007/s10100-023-00891-z
Raphael Herding, Lars Mönch
Abstract Demand fulfillment and order management are important functions in semiconductor supply chains to interact with customers. In this paper, an iterative short-term demand supply matching (STDSM) algorithm based on mixed-integer linear programming (MILP) is proposed. This approach repromises orders taking into account the finite capacity of the shop floor. Decomposition is used to obtain computationally tractable subproblems. The STDSM approach is applied together with master planning and allocation planning in a rolling horizon setting. A simulation model of a simplified semiconductor supply chain is used for the rolling horizon experiments. The experiments demonstrate that the proposed STDSM scheme outperforms conventional business rule-based heuristics with respect to several delivery performance-related measures and with respect to stability.
{"title":"A rolling horizon planning approach for short-term demand supply matching","authors":"Raphael Herding, Lars Mönch","doi":"10.1007/s10100-023-00891-z","DOIUrl":"https://doi.org/10.1007/s10100-023-00891-z","url":null,"abstract":"Abstract Demand fulfillment and order management are important functions in semiconductor supply chains to interact with customers. In this paper, an iterative short-term demand supply matching (STDSM) algorithm based on mixed-integer linear programming (MILP) is proposed. This approach repromises orders taking into account the finite capacity of the shop floor. Decomposition is used to obtain computationally tractable subproblems. The STDSM approach is applied together with master planning and allocation planning in a rolling horizon setting. A simulation model of a simplified semiconductor supply chain is used for the rolling horizon experiments. The experiments demonstrate that the proposed STDSM scheme outperforms conventional business rule-based heuristics with respect to several delivery performance-related measures and with respect to stability.","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"6 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136161064","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 : 2023-10-27DOI: 10.1007/s10100-023-00889-7
Gustav Feichtinger, Dieter Grass, Peter M. Kort, Andreas J. Novak, Andrea Seidl, Stefan Wrzaczek
{"title":"How Hartl exceeds Skiba: determinants of a successful career in academia","authors":"Gustav Feichtinger, Dieter Grass, Peter M. Kort, Andreas J. Novak, Andrea Seidl, Stefan Wrzaczek","doi":"10.1007/s10100-023-00889-7","DOIUrl":"https://doi.org/10.1007/s10100-023-00889-7","url":null,"abstract":"","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136317173","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 : 2023-10-27DOI: 10.1007/s10100-023-00890-0
A. Zapata, A. M. Mármol, L. Monroy, M. A. Caraballo
Abstract This paper analyses the impact of altruism on the individual country goverments’ incentives to reduce global polluting emissions. The game theory perspective provides insights into the strategic decision-making processes of the governments regarding the problem of climate change. We propose a model of strategic interactions among countries in which each government is concerned with its own benefit, as well as with the benefits of all the other countries.The model is a vector-valued non-cooperative game that permits the representation of situations in which the preferences of the governments are incomplete and there is imprecision about the degrees of altruism. The focus is on the identification of the potential equilibria that will eventually be reached when the governments show different attitudes towards other countries or groups of countries. As a result, we show that the incorporation of altruism into the model produces equilibria with a positive effect on the reduction of emissions.
{"title":"Altruistic preferences in global emission games","authors":"A. Zapata, A. M. Mármol, L. Monroy, M. A. Caraballo","doi":"10.1007/s10100-023-00890-0","DOIUrl":"https://doi.org/10.1007/s10100-023-00890-0","url":null,"abstract":"Abstract This paper analyses the impact of altruism on the individual country goverments’ incentives to reduce global polluting emissions. The game theory perspective provides insights into the strategic decision-making processes of the governments regarding the problem of climate change. We propose a model of strategic interactions among countries in which each government is concerned with its own benefit, as well as with the benefits of all the other countries.The model is a vector-valued non-cooperative game that permits the representation of situations in which the preferences of the governments are incomplete and there is imprecision about the degrees of altruism. The focus is on the identification of the potential equilibria that will eventually be reached when the governments show different attitudes towards other countries or groups of countries. As a result, we show that the incorporation of altruism into the model produces equilibria with a positive effect on the reduction of emissions.","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"228 1-4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136261926","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 : 2023-10-27DOI: 10.1007/s10100-023-00881-1
Kolos Cs. Ágoston, Marianna E.-Nagy
Abstract The minimum sum-of-squares clusering is the most widely used clustering method. The minimum sum-of-squares clustering is usually solved by the heuristic KMEANS algorithm, which converges to a local optimum. A lot of effort has been made to solve such kind of problems, but a mixed integer linear programming formulation (MILP) is still missing. In this paper, we formulate MILP models. The advantage of MILP formulation is that users can extend the original problem with arbitrary linear constraints. We also present numerical results, we solve these models up to sample size of 150.
{"title":"Mixed integer linear programming formulation for K-means clustering problem","authors":"Kolos Cs. Ágoston, Marianna E.-Nagy","doi":"10.1007/s10100-023-00881-1","DOIUrl":"https://doi.org/10.1007/s10100-023-00881-1","url":null,"abstract":"Abstract The minimum sum-of-squares clusering is the most widely used clustering method. The minimum sum-of-squares clustering is usually solved by the heuristic KMEANS algorithm, which converges to a local optimum. A lot of effort has been made to solve such kind of problems, but a mixed integer linear programming formulation (MILP) is still missing. In this paper, we formulate MILP models. The advantage of MILP formulation is that users can extend the original problem with arbitrary linear constraints. We also present numerical results, we solve these models up to sample size of 150.","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136311460","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 : 2023-10-13DOI: 10.1007/s10100-023-00883-z
Michael Manitz, Marc-Philip Piehl
Abstract Ensuring customer satisfaction is one of the main objectives of a call center. We focus on the question of how many agents are necessary and how they should be allocated to maintain a service level threshold and reduce the expected waiting time of the customers. In this paper, we consider a multistage call center that consists of a front and a back office, impatient customers, and an overflow mechanism. Based on the performance evaluation of such a system using a continuous-time Markov chain, a configuration of agents is determined using a binary search algorithm. We focus on structural insights, e.g., convexity conditions, to obtain a quick solution for the staffing problem. Since monotonicity does not always hold, the approach is heuristic. The numerical results show the performance of the algorithm. The influence of the fraction requiring second-level service in the back office and the impatience rate for the minimum number of agents is shown.
{"title":"A fast staffing algorithm for multistage call centers with impatient customers and time-dependent overflow","authors":"Michael Manitz, Marc-Philip Piehl","doi":"10.1007/s10100-023-00883-z","DOIUrl":"https://doi.org/10.1007/s10100-023-00883-z","url":null,"abstract":"Abstract Ensuring customer satisfaction is one of the main objectives of a call center. We focus on the question of how many agents are necessary and how they should be allocated to maintain a service level threshold and reduce the expected waiting time of the customers. In this paper, we consider a multistage call center that consists of a front and a back office, impatient customers, and an overflow mechanism. Based on the performance evaluation of such a system using a continuous-time Markov chain, a configuration of agents is determined using a binary search algorithm. We focus on structural insights, e.g., convexity conditions, to obtain a quick solution for the staffing problem. Since monotonicity does not always hold, the approach is heuristic. The numerical results show the performance of the algorithm. The influence of the fraction requiring second-level service in the back office and the impatience rate for the minimum number of agents is shown.","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135853081","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 : 2023-10-12DOI: 10.1007/s10100-023-00886-w
Raouf Boucekkine, Fouad El Ouardighi, Konstantin Kogan
{"title":"Recycling of multi-source waste in an aggregate circular economy","authors":"Raouf Boucekkine, Fouad El Ouardighi, Konstantin Kogan","doi":"10.1007/s10100-023-00886-w","DOIUrl":"https://doi.org/10.1007/s10100-023-00886-w","url":null,"abstract":"","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135968402","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 : 2023-09-30DOI: 10.1007/s10100-023-00884-y
Ana Klobučar Barišić, Robert Manger
{"title":"Solving the minimum-cost double Roman domination problem","authors":"Ana Klobučar Barišić, Robert Manger","doi":"10.1007/s10100-023-00884-y","DOIUrl":"https://doi.org/10.1007/s10100-023-00884-y","url":null,"abstract":"","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136341455","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 : 2023-09-28DOI: 10.1007/s10100-023-00882-0
E. Angelelli, V. Morandi, M. G. Speranza
Abstract In this paper, we consider the case of companies that offer a demand-responsive transportation service, such as a shared-taxi service, and are engaged in a horizontal collaboration initiative. The goal of the coalition is to optimize the transportation operations in such a way that no company is penalized, in terms of customers served and/or working time. We present an optimization model for a multi-day planning horizon that includes constraints aimed at guaranteeing a level of fairness to all companies that can be controlled over the planning horizon and day-by-day, if beneficial. An adaptive large neighborhood search heuristic is then presented for its solution. The computational experiments show that, although the model constraints the optimization space, it still guarantees substantial savings. Moreover, they show that the model is flexible and can guarantee the sustainability in the long term of the collaboration initiative.
{"title":"Multi-day fair collaboration in demand-responsive transportation","authors":"E. Angelelli, V. Morandi, M. G. Speranza","doi":"10.1007/s10100-023-00882-0","DOIUrl":"https://doi.org/10.1007/s10100-023-00882-0","url":null,"abstract":"Abstract In this paper, we consider the case of companies that offer a demand-responsive transportation service, such as a shared-taxi service, and are engaged in a horizontal collaboration initiative. The goal of the coalition is to optimize the transportation operations in such a way that no company is penalized, in terms of customers served and/or working time. We present an optimization model for a multi-day planning horizon that includes constraints aimed at guaranteeing a level of fairness to all companies that can be controlled over the planning horizon and day-by-day, if beneficial. An adaptive large neighborhood search heuristic is then presented for its solution. The computational experiments show that, although the model constraints the optimization space, it still guarantees substantial savings. Moreover, they show that the model is flexible and can guarantee the sustainability in the long term of the collaboration initiative.","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135387277","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 : 2023-09-26DOI: 10.1007/s10100-023-00885-x
Imre Dimény, Tamás Koltai
Abstract The objective of Assembly Line Balancing (ALB) is to find the proper assignment of tasks to workstations, taking into consideration various types of constraints and defined management goals. Early research in the field focused on solving the Simple Assembly Line Balancing problem, a basic simplified version of the general problem. As the production environment became more complex, several new ALB problem types appeared, and almost all ALB problems are NP-hard, meaning that finding a solution requires a lot of time, resources, and computational power. Methods with custom-made algorithms and generic approaches have been developed for solving these problems. While custom-made algorithms are generally more efficient, generic approaches can be more easily extended to cover other variations of the problem. Over the past few decades, automation has played an increasingly important role in various operations, although complete automation is often not possible. As a result, there is a growing need for partially automated assembly line balancing models. In these circumstances, the flexibility of a generic approach is essential. This paper compares two generic approaches: mixed integer linear programming (MILP) and constraint programming (CP), for two types of partially automated assembly line balancing problems. While CP is relatively slower in solving the simpler allocation problems, it is more efficient than MILP when an increased number of constraints is applied to the ALB and an allocation and scheduling problem needs to be solved.
{"title":"Comparison of MILP and CP models for balancing partially automated assembly lines","authors":"Imre Dimény, Tamás Koltai","doi":"10.1007/s10100-023-00885-x","DOIUrl":"https://doi.org/10.1007/s10100-023-00885-x","url":null,"abstract":"Abstract The objective of Assembly Line Balancing (ALB) is to find the proper assignment of tasks to workstations, taking into consideration various types of constraints and defined management goals. Early research in the field focused on solving the Simple Assembly Line Balancing problem, a basic simplified version of the general problem. As the production environment became more complex, several new ALB problem types appeared, and almost all ALB problems are NP-hard, meaning that finding a solution requires a lot of time, resources, and computational power. Methods with custom-made algorithms and generic approaches have been developed for solving these problems. While custom-made algorithms are generally more efficient, generic approaches can be more easily extended to cover other variations of the problem. Over the past few decades, automation has played an increasingly important role in various operations, although complete automation is often not possible. As a result, there is a growing need for partially automated assembly line balancing models. In these circumstances, the flexibility of a generic approach is essential. This paper compares two generic approaches: mixed integer linear programming (MILP) and constraint programming (CP), for two types of partially automated assembly line balancing problems. While CP is relatively slower in solving the simpler allocation problems, it is more efficient than MILP when an increased number of constraints is applied to the ALB and an allocation and scheduling problem needs to be solved.","PeriodicalId":9689,"journal":{"name":"Central European Journal of Operations Research","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134960351","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}
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