An uncertain furniture production planning problem with cumulative service levels
To investigate how the loss averse customer’s psychological satisfaction affects the company’s furniture production planning, we establish a furniture production planning model under uncertain environment, where customer demand and production costs are characterized by mutually independent uncertain...
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| Vydáno v: | Soft computing (Berlin, Germany) Ročník 21; číslo 4; s. 1041 - 1055 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.02.2017
Springer Nature B.V |
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| ISSN: | 1432-7643, 1433-7479 |
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| Abstract | To investigate how the loss averse customer’s psychological satisfaction affects the company’s furniture production planning, we establish a furniture production planning model under uncertain environment, where customer demand and production costs are characterized by mutually independent uncertain variables. Based on prospect theory, customer’s psychological satisfaction about stockout performance is measured by cumulative service levels in our model. In the framework of uncertainty theory, the proposed uncertain model can be transformed into an equivalent deterministic form. However, the transformed model is a nonlinear mixed integer programming problem, which cannot be solved by conventional optimization algorithms. To cope with this difficulty, a chemical reaction optimization algorithm integrated with LINGO software is designed to solve the proposed production planning problem. In order to verify the effectiveness of the designed hybrid chemical reaction optimization (CRO) algorithm, we conduct several numerical experiments via an application example and compare with a spanning tree-based genetic algorithm (hst-GA). The computational results show that our proposed CRO algorithm achieves better performance than hst-GA, and the results also provide several interesting managerial insights in production planning problems. |
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| AbstractList | To investigate how the loss averse customer’s psychological satisfaction affects the company’s furniture production planning, we establish a furniture production planning model under uncertain environment, where customer demand and production costs are characterized by mutually independent uncertain variables. Based on prospect theory, customer’s psychological satisfaction about stockout performance is measured by cumulative service levels in our model. In the framework of uncertainty theory, the proposed uncertain model can be transformed into an equivalent deterministic form. However, the transformed model is a nonlinear mixed integer programming problem, which cannot be solved by conventional optimization algorithms. To cope with this difficulty, a chemical reaction optimization algorithm integrated with LINGO software is designed to solve the proposed production planning problem. In order to verify the effectiveness of the designed hybrid chemical reaction optimization (CRO) algorithm, we conduct several numerical experiments via an application example and compare with a spanning tree-based genetic algorithm (hst-GA). The computational results show that our proposed CRO algorithm achieves better performance than hst-GA, and the results also provide several interesting managerial insights in production planning problems. |
| Author | Tang, Wansheng Yang, Guoqing Zhao, Ruiqing |
| Author_xml | – sequence: 1 givenname: Guoqing surname: Yang fullname: Yang, Guoqing organization: Institute of Systems Engineering, Tianjin University – sequence: 2 givenname: Wansheng surname: Tang fullname: Tang, Wansheng email: tang@tju.edu.cn organization: Institute of Systems Engineering, Tianjin University – sequence: 3 givenname: Ruiqing surname: Zhao fullname: Zhao, Ruiqing organization: Institute of Systems Engineering, Tianjin University |
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| Keywords | Prospect theory Furniture production planning Chemical reaction optimization Cumulative service level Uncertainty theory Loss aversion |
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| SubjectTerms | Algorithms Artificial Intelligence Behavior Chemical reactions Computational Intelligence Control Customer satisfaction Customer services Customers Decision making Design Engineering Furniture industry Genetic algorithms Graph theory Independent variables Integer programming Linear programming Mathematical Logic and Foundations Mathematical programming Mechatronics Methodologies and Application Mixed integer Optimization Production costs Production planning Random variables Robotics Subject specialists |
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| Title | An uncertain furniture production planning problem with cumulative service levels |
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