Ikpe Justice Akpan, Yawo M. Kobara, Josiah Owolabi, Asuama A. Akpan, Onyebuchi Felix Offodile
Artificial intelligence (AI) as a disruptive technology is not new. However, its recent evolution, engineered by technological transformation, big data analytics, and quantum computing, produces conversational and generative AI (CGAI/GenAI) and human‐like chatbots that disrupt conventional operations and methods in different fields. This study investigates the scientific landscape of CGAI and human–chatbot interaction/collaboration and evaluates use cases, benefits, challenges, and policy implications for multidisciplinary education and allied industry operations. The publications trend showed that just 4% (n = 75) occurred during 2006–2018, while 2019–2023 experienced astronomical growth (n = 1763 or 96%). The prominent use cases of CGAI (e.g., ChatGPT) for teaching, learning, and research activities occurred in computer science (multidisciplinary and AI; 32%), medical/healthcare (17%), engineering (7%), and business fields (6%). The intellectual structure shows strong collaboration among eminent multidisciplinary sources in business, information systems, and other areas. The thematic structure highlights prominent CGAI use cases, including improved user experience in human–computer interaction, computer programs/code generation, and systems creation. Widespread CGAI usefulness for teachers, researchers, and learners includes syllabi/course content generation, testing aids, and academic writing. The concerns about abuse and misuse (plagiarism, academic integrity, privacy violations) and issues about misinformation, danger of self‐diagnoses, and patient privacy in medical/healthcare applications are prominent. Formulating strategies and policies to address potential CGAI challenges in teaching/learning and practice are priorities. Developing discipline‐based automatic detection of GenAI contents to check abuse is proposed. In operational/operations research areas, proper CGAI/GenAI integration with modeling and decision support systems requires further studies.
{"title":"Conversational and generative artificial intelligence and human–chatbot interaction in education and research","authors":"Ikpe Justice Akpan, Yawo M. Kobara, Josiah Owolabi, Asuama A. Akpan, Onyebuchi Felix Offodile","doi":"10.1111/itor.13522","DOIUrl":"https://doi.org/10.1111/itor.13522","url":null,"abstract":"Artificial intelligence (AI) as a disruptive technology is not new. However, its recent evolution, engineered by technological transformation, big data analytics, and quantum computing, produces conversational and generative AI (CGAI/GenAI) and human‐like chatbots that disrupt conventional operations and methods in different fields. This study investigates the scientific landscape of CGAI and human–chatbot interaction/collaboration and evaluates use cases, benefits, challenges, and policy implications for multidisciplinary education and allied industry operations. The publications trend showed that just 4% (<jats:italic>n</jats:italic> = 75) occurred during 2006–2018, while 2019–2023 experienced astronomical growth (<jats:italic>n</jats:italic> = 1763 or 96%). The prominent use cases of CGAI (e.g., ChatGPT) for teaching, learning, and research activities occurred in computer science (multidisciplinary and AI; 32%), medical/healthcare (17%), engineering (7%), and business fields (6%). The intellectual structure shows strong collaboration among eminent multidisciplinary sources in business, information systems, and other areas. The thematic structure highlights prominent CGAI use cases, including improved user experience in human–computer interaction, computer programs/code generation, and systems creation. Widespread CGAI usefulness for teachers, researchers, and learners includes syllabi/course content generation, testing aids, and academic writing. The concerns about abuse and misuse (plagiarism, academic integrity, privacy violations) and issues about misinformation, danger of self‐diagnoses, and patient privacy in medical/healthcare applications are prominent. Formulating strategies and policies to address potential CGAI challenges in teaching/learning and practice are priorities. Developing discipline‐based automatic detection of GenAI contents to check abuse is proposed. In operational/operations research areas, proper CGAI/GenAI integration with modeling and decision support systems requires further studies.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"76 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141863720","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}
Designing a product line that considers value‐added services (VASs) is a strategic move for enterprises with diversified customer needs. Additionally, a dynamic pricing strategy that can respond to changes in the external environment is crucial for enterprises. This study investigates product and VAS price adjustments for enterprises in monopolistic and oligopolistic competitive environments, respectively, based on the multinomial logit model. A two‐stage pricing model is developed for products and services to obtain the optimal pricing strategy. The findings reveal that customers’ strategic behaviors significantly impact on enterprises’ pricing decisions. When adjusting prices, enterprises need to consider the strategic behaviors of customers to ensure the rationality of pricing. Furthermore, irrespective of the competitive environment faced by enterprises, there is a need to emphasize the importance of dynamic pricing. Making appropriate adjustments to prices in the second stage can, overall, enhance the profitability of the enterprise.
{"title":"Two‐stage pricing of products and services considering different competitive environments","authors":"Wei Qi, Ziwei Li, Xuwang Liu","doi":"10.1111/itor.13520","DOIUrl":"https://doi.org/10.1111/itor.13520","url":null,"abstract":"Designing a product line that considers value‐added services (VASs) is a strategic move for enterprises with diversified customer needs. Additionally, a dynamic pricing strategy that can respond to changes in the external environment is crucial for enterprises. This study investigates product and VAS price adjustments for enterprises in monopolistic and oligopolistic competitive environments, respectively, based on the multinomial logit model. A two‐stage pricing model is developed for products and services to obtain the optimal pricing strategy. The findings reveal that customers’ strategic behaviors significantly impact on enterprises’ pricing decisions. When adjusting prices, enterprises need to consider the strategic behaviors of customers to ensure the rationality of pricing. Furthermore, irrespective of the competitive environment faced by enterprises, there is a need to emphasize the importance of dynamic pricing. Making appropriate adjustments to prices in the second stage can, overall, enhance the profitability of the enterprise.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"17 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141776975","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}
The knapsack problem (KP) with forfeits is a generalized KP that aims to select some items, among a set of candidate items, to maximize a profit function without exceeding the knapsack capacity. Moreover, a forfeit cost is incurred and deducted from the profit function when both incompatible items are placed in the knapsack. This problem is a relevant model for a number of applications and is however computationally challenging. We present a hybrid heuristic method for tackling this problem that combines the evolutionary search with adaptive feasible and infeasible search to find high‐quality solutions. A streamlining technique is designed to accelerate the evaluation of candidate solutions, which increases significantly the computational efficiency of the algorithm. We assess the algorithm on 120 test instances and demonstrate its dominance over the best performing approaches in the literature. Particularly, we show 94 improved lower bounds. We investigate the essential algorithmic components to understand their roles.
{"title":"Adaptive feasible and infeasible evolutionary search for the knapsack problem with forfeits","authors":"Qing Zhou, Jin‐Kao Hao, Zhong‐Zhong Jiang, Qinghua Wu","doi":"10.1111/itor.13512","DOIUrl":"https://doi.org/10.1111/itor.13512","url":null,"abstract":"The knapsack problem (KP) with forfeits is a generalized KP that aims to select some items, among a set of candidate items, to maximize a profit function without exceeding the knapsack capacity. Moreover, a forfeit cost is incurred and deducted from the profit function when both incompatible items are placed in the knapsack. This problem is a relevant model for a number of applications and is however computationally challenging. We present a hybrid heuristic method for tackling this problem that combines the evolutionary search with adaptive feasible and infeasible search to find high‐quality solutions. A streamlining technique is designed to accelerate the evaluation of candidate solutions, which increases significantly the computational efficiency of the algorithm. We assess the algorithm on 120 test instances and demonstrate its dominance over the best performing approaches in the literature. Particularly, we show 94 improved lower bounds. We investigate the essential algorithmic components to understand their roles.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"2 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141776974","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}
A. Saavedra‐Nieves, M. A. Mosquera, M. G. Fiestras‐Janeiro
This paper innovatively addresses the effect of cooperation on sequencing situations with position‐dependent effects. Specifically, we ensure the convexity of the associated sequencing games under the fulfillment of certain conditions related to the neighbor switching gains. Additionally, we propose two families of allocation rules based on sharing the neighbor switching gains under two distinct procedures, each providing a path from the initial order to an optimal order. From a theoretical point of view, an axiomatization of both families of allocations is provided, and their stability is also ensured under the conditions related to convexity.
{"title":"Sequencing situations with position‐dependent effects under cooperation","authors":"A. Saavedra‐Nieves, M. A. Mosquera, M. G. Fiestras‐Janeiro","doi":"10.1111/itor.13518","DOIUrl":"https://doi.org/10.1111/itor.13518","url":null,"abstract":"This paper innovatively addresses the effect of cooperation on sequencing situations with position‐dependent effects. Specifically, we ensure the convexity of the associated sequencing games under the fulfillment of certain conditions related to the neighbor switching gains. Additionally, we propose two families of allocation rules based on sharing the neighbor switching gains under two distinct procedures, each providing a path from the initial order to an optimal order. From a theoretical point of view, an axiomatization of both families of allocations is provided, and their stability is also ensured under the conditions related to convexity.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"48 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141776978","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}
Wenbo Li, Bin Dan, Xumei Zhang, Ting Lei, Shengming Zhang
Many third‐party platforms for shared manufacturing (platforms) have developed rapidly in recent years. The quality admission and pricing of production capacity are crucial issues for these platforms. This paper focuses on the platform supply chain composed of a platform, multiple manufacturers with surplus production capacity (sharers), and multiple manufacturers with insufficient production capacity (renters). Considering the impact of the production capacity quality on the shared scale and rental demand of production capacity, this paper constructs a game model for the platform supply chain under different quality admission scenarios, investigates the quality admission and price decisions of production capacity on the platform, and analyses the impact of the quality admission on the sharers’ and renters’ profits. The results show that the platform sets the quality admission when the sharers’ production capacity scale is small and the platform regulatory cost is low. The platform always increases its service price but may reduce the rental price of production capacity under the quality admission scenario. When the sharers’ production capacity scale is large, the platform lowers the threshold of quality admission with the quality elasticity of production capacity increasing. In addition, when the quality elasticity of production capacity and platform regulatory cost are low, and the sharers’ production capacity scale is small, the quality admission of the platform realizes the win–win–win situation for the platform, renters, and sharers.
{"title":"The quality admission and price decisions of production capacity on the third‐party platform for shared manufacturing","authors":"Wenbo Li, Bin Dan, Xumei Zhang, Ting Lei, Shengming Zhang","doi":"10.1111/itor.13517","DOIUrl":"https://doi.org/10.1111/itor.13517","url":null,"abstract":"Many third‐party platforms for shared manufacturing (platforms) have developed rapidly in recent years. The quality admission and pricing of production capacity are crucial issues for these platforms. This paper focuses on the platform supply chain composed of a platform, multiple manufacturers with surplus production capacity (sharers), and multiple manufacturers with insufficient production capacity (renters). Considering the impact of the production capacity quality on the shared scale and rental demand of production capacity, this paper constructs a game model for the platform supply chain under different quality admission scenarios, investigates the quality admission and price decisions of production capacity on the platform, and analyses the impact of the quality admission on the sharers’ and renters’ profits. The results show that the platform sets the quality admission when the sharers’ production capacity scale is small and the platform regulatory cost is low. The platform always increases its service price but may reduce the rental price of production capacity under the quality admission scenario. When the sharers’ production capacity scale is large, the platform lowers the threshold of quality admission with the quality elasticity of production capacity increasing. In addition, when the quality elasticity of production capacity and platform regulatory cost are low, and the sharers’ production capacity scale is small, the quality admission of the platform realizes the win–win–win situation for the platform, renters, and sharers.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"16 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141776882","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}
Tarley Mansur Fantazzini, Thiago Vieira, Reinaldo Morabito, Pedro Munari
We address the aircraft recovery problem faced by a Brazilian oil and gas company during its offshore operations. This problem involves hiring helicopters from an outsourced company to transport personnel from an airport to maritime units. The performed flights are subject to disruptions and might require rescheduling. To assist with decision‐making in such situations, we introduce a discrete‐time integer linear programming (ILP) model that considers company‐specific attributes, including a lexicographic objective function that prioritizes (i) the reduction of flight transfers to the next day; (ii) the reduction of helicopter utilization; and (iii) the reduction of flight delays of the day. We develop four different solution approaches using hierarchical goal programming based on the proposed model, aided by enhancements and valid inequalities. Computational experiments using both real‐world and simulated instances demonstrate that our approaches can provide effective solutions for most instances using a general‐purpose ILP solver within acceptable computation times.
{"title":"Hierarchical goal programming approaches to solve a discrete‐time formulation for the aircraft recovery problem of a Brazilian oil and gas company","authors":"Tarley Mansur Fantazzini, Thiago Vieira, Reinaldo Morabito, Pedro Munari","doi":"10.1111/itor.13516","DOIUrl":"https://doi.org/10.1111/itor.13516","url":null,"abstract":"We address the aircraft recovery problem faced by a Brazilian oil and gas company during its offshore operations. This problem involves hiring helicopters from an outsourced company to transport personnel from an airport to maritime units. The performed flights are subject to disruptions and might require rescheduling. To assist with decision‐making in such situations, we introduce a discrete‐time integer linear programming (ILP) model that considers company‐specific attributes, including a lexicographic objective function that prioritizes (i) the reduction of flight transfers to the next day; (ii) the reduction of helicopter utilization; and (iii) the reduction of flight delays of the day. We develop four different solution approaches using hierarchical goal programming based on the proposed model, aided by enhancements and valid inequalities. Computational experiments using both real‐world and simulated instances demonstrate that our approaches can provide effective solutions for most instances using a general‐purpose ILP solver within acceptable computation times.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"44 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745883","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}
Fatmah Almathkour, Youcef Magnouche, A. Ridha Mahjoub, Raouia Taktak
In this paper, we consider the survivable network design problem when the connectivity types are in {0, 1, 2, 3}. The problem has wide applications in telecommunication networks. We consider the problem from a polyhedral point of view. We describe several classes of valid inequalities and give necessary conditions and sufficient conditions for these inequalities to be facet defining. We also develop separation routines for these inequalities. Using these results, we devise a branch-and-cut algorithm along with an extensive computational study is presented.
{"title":"Design of survivable networks with low connectivity requirements","authors":"Fatmah Almathkour, Youcef Magnouche, A. Ridha Mahjoub, Raouia Taktak","doi":"10.1111/itor.13511","DOIUrl":"10.1111/itor.13511","url":null,"abstract":"<p>In this paper, we consider the survivable network design problem when the connectivity types are in {0, 1, 2, 3}. The problem has wide applications in telecommunication networks. We consider the problem from a polyhedral point of view. We describe several classes of valid inequalities and give necessary conditions and sufficient conditions for these inequalities to be facet defining. We also develop separation routines for these inequalities. Using these results, we devise a branch-and-cut algorithm along with an extensive computational study is presented.</p>","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"32 2","pages":"918-960"},"PeriodicalIF":3.1,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141739978","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}
In this work, a Fermatean fuzzy (FF) multi‐objective indefinite quadratic transportation problem (TP) is introduced. Due to some unavoidable reasons, real‐life transportation parameters such as supply, demand and costs are indeterminate in nature and cannot be expressed in crisp terms. We represent these parameters using FF numbers, an extension of fuzzy numbers, which are capable of representing indeterminacy efficiently. A multi‐objective indefinite quadratic TP where each objective is a product of two linear factors (cost functions) is considered. Defuzzification of FF numbers is accomplished by the introduction of ‐cut for the first time. The obtained crisp TP is solved using the intuitionistic fuzzy programming approach and FF programming approach to arrive at a compromise solution. To substantiate the work, solution methodology based on defuzzification using the ranking function is also deliberated. The applicability of the model is demonstrated through a sustainable TP, which simultaneously minimizes transportation cost with depreciation cost and packaging cost with wastage cost. The resulting value of the objective functions and the aspiration levels are compared to depict the efficacy of the proposed method over the ranking function method. The concluding section summarizes the work, and future avenues along with some limitations of the work are also specified.
{"title":"A new Fermatean fuzzy multi‐objective indefinite quadratic transportation problem with an application to sustainable transportation","authors":"Aakanksha Singh, Ritu Arora, Shalini Arora","doi":"10.1111/itor.13513","DOIUrl":"https://doi.org/10.1111/itor.13513","url":null,"abstract":"In this work, a Fermatean fuzzy (FF) multi‐objective indefinite quadratic transportation problem (TP) is introduced. Due to some unavoidable reasons, real‐life transportation parameters such as supply, demand and costs are indeterminate in nature and cannot be expressed in crisp terms. We represent these parameters using FF numbers, an extension of fuzzy numbers, which are capable of representing indeterminacy efficiently. A multi‐objective indefinite quadratic TP where each objective is a product of two linear factors (cost functions) is considered. Defuzzification of FF numbers is accomplished by the introduction of ‐cut for the first time. The obtained crisp TP is solved using the intuitionistic fuzzy programming approach and FF programming approach to arrive at a compromise solution. To substantiate the work, solution methodology based on defuzzification using the ranking function is also deliberated. The applicability of the model is demonstrated through a sustainable TP, which simultaneously minimizes transportation cost with depreciation cost and packaging cost with wastage cost. The resulting value of the objective functions and the aspiration levels are compared to depict the efficacy of the proposed method over the ranking function method. The concluding section summarizes the work, and future avenues along with some limitations of the work are also specified.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"10 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141739979","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}
We present the problem of a regional airline based at a slot‐constrained airport, which must select a set of destinations to serve, how many flights per day to operate to each destination, at what time the flights take place and which aircraft operates each flight. Restricting ourselves to the special case of regional airlines, which fly round trips from a central hub, we are able to tackle the four above decisions jointly. By contrast, in the existing literature, these decisions are usually optimised separately for generic airline networks. To solve the proposed problem, we introduce two compact integer formulations: a three‐index and a two‐index formulation. This latter, however, only solves a relaxation of the original problem because it cannot guarantee that all constraints are respected. Therefore, we embed the two‐index formulation into an iterative algorithm which dynamically adds violated constraints. Computational experiments highlight the validity of this approach and provide insights into the characteristics of the solutions.
{"title":"Destination selection and flight scheduling for regional airlines at slot‐constrained airports","authors":"Alberto Santini","doi":"10.1111/itor.13505","DOIUrl":"https://doi.org/10.1111/itor.13505","url":null,"abstract":"We present the problem of a regional airline based at a slot‐constrained airport, which must select a set of destinations to serve, how many flights per day to operate to each destination, at what time the flights take place and which aircraft operates each flight. Restricting ourselves to the special case of regional airlines, which fly round trips from a central hub, we are able to tackle the four above decisions jointly. By contrast, in the existing literature, these decisions are usually optimised separately for generic airline networks. To solve the proposed problem, we introduce two compact integer formulations: a three‐index and a two‐index formulation. This latter, however, only solves a relaxation of the original problem because it cannot guarantee that all constraints are respected. Therefore, we embed the two‐index formulation into an iterative algorithm which dynamically adds violated constraints. Computational experiments highlight the validity of this approach and provide insights into the characteristics of the solutions.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"36 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569502","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}
Francisco Yuraszeck, Gonzalo Mejía, Armin Lüer‐Villagra
In this paper, we study the group shop and the mixed shop scheduling problems with single and identical parallel machines at each workstation with the makespan criterion. We adapted a constraint programming formulation previously presented for the classical resource‐constrained project scheduling problem. The effectiveness of our approach is evident in the fact that it achieved optimality in 107 out of 130 classical group shop scheduling problem instances and in 320 classical mixed shop scheduling problem instances. In the last set, we obtained 13 new optimal solutions.
{"title":"An adapted constraint‐programming formulation of the resource‐constrained project scheduling problem applied to the identical parallel machines group shop and mixed shop scheduling problems","authors":"Francisco Yuraszeck, Gonzalo Mejía, Armin Lüer‐Villagra","doi":"10.1111/itor.13504","DOIUrl":"https://doi.org/10.1111/itor.13504","url":null,"abstract":"In this paper, we study the group shop and the mixed shop scheduling problems with single and identical parallel machines at each workstation with the makespan criterion. We adapted a constraint programming formulation previously presented for the classical resource‐constrained project scheduling problem. The effectiveness of our approach is evident in the fact that it achieved optimality in 107 out of 130 classical group shop scheduling problem instances and in 320 classical mixed shop scheduling problem instances. In the last set, we obtained 13 new optimal solutions.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"15 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569503","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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