Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment
<p><strong>Purpose:</strong> The aim of this paper is to deal with the supply chain management (SCM) with quantity discount policy under the complex fuzzy environment, which is characterized as the bi-fuzzy variables. By taking into account the strategy and the process of decision...
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| Format: | Article |
| Language: | English |
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OmniaScience
2014-06-01
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| Series: | Journal of Industrial Engineering and Management |
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| Online Access: | http://www.jiem.org/index.php/jiem/article/view/1079 |
| _version_ | 1828525666243444736 |
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| author | Zhe Zhang Jiuping Xu |
| author_facet | Zhe Zhang Jiuping Xu |
| author_sort | Zhe Zhang |
| collection | DOAJ |
| description | <p><strong>Purpose:</strong> The aim of this paper is to deal with the supply chain management (SCM) with quantity discount policy under the complex fuzzy environment, which is characterized as the bi-fuzzy variables. By taking into account the strategy and the process of decision making, a bi-fuzzy nonlinear multiple objective decision making (MODM) model is presented to solve the proposed problem.</p><p><strong>Design/methodology/approach: </strong>The bi-fuzzy variables in the MODM model are transformed into the trapezoidal fuzzy variables by the DMs's degree of optimism ?1 and ?2, which are de-fuzzified by the expected value index subsequently. For solving the complex nonlinear model, a multi-objective adaptive particle swarm optimization algorithm (MO-APSO) is designed as the solution method.</p><p><strong>Findings:</strong> The proposed model and algorithm are applied to a typical example of SCM problem to illustrate the effectiveness. Based on the sensitivity analysis of the results, the bi-fuzzy nonlinear MODM SCM model is proved to be sensitive to the possibility level ?1.</p><p><strong>Practical implications:</strong> The study focuses on the SCM under complex fuzzy environment in SCM, which has a great practical significance. Therefore, the bi-fuzzy MODM model and MO-APSO can be further applied in SCM problem with quantity discount policy.</p><p><strong>Originality/value:</strong> The bi-fuzzy variable is employed in the nonlinear MODM model of SCM to characterize the hybrid uncertain environment, and this work is original. In addition, the hybrid crisp approach is proposed to transferred to model to an equivalent crisp one by the DMs's degree of optimism and the expected value index. Since the MODM model consider the bi-fuzzy environment and quantity discount policy, so this paper has a great practical significance.</p> |
| first_indexed | 2024-12-11T21:11:01Z |
| format | Article |
| id | doaj.art-54c127456c5c45e38d72e4257c25934e |
| institution | Directory Open Access Journal |
| issn | 2013-8423 2013-0953 |
| language | English |
| last_indexed | 2024-12-11T21:11:01Z |
| publishDate | 2014-06-01 |
| publisher | OmniaScience |
| record_format | Article |
| series | Journal of Industrial Engineering and Management |
| spelling | doaj.art-54c127456c5c45e38d72e4257c25934e2022-12-22T00:50:44ZengOmniaScienceJournal of Industrial Engineering and Management2013-84232013-09532014-06-017366068010.3926/jiem.1079272Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environmentZhe Zhang0Jiuping Xu1School Economics & Management, Nanjing University of Science and TechnologyUncertainty Decision-Making Laboratory, Sichuan University<p><strong>Purpose:</strong> The aim of this paper is to deal with the supply chain management (SCM) with quantity discount policy under the complex fuzzy environment, which is characterized as the bi-fuzzy variables. By taking into account the strategy and the process of decision making, a bi-fuzzy nonlinear multiple objective decision making (MODM) model is presented to solve the proposed problem.</p><p><strong>Design/methodology/approach: </strong>The bi-fuzzy variables in the MODM model are transformed into the trapezoidal fuzzy variables by the DMs's degree of optimism ?1 and ?2, which are de-fuzzified by the expected value index subsequently. For solving the complex nonlinear model, a multi-objective adaptive particle swarm optimization algorithm (MO-APSO) is designed as the solution method.</p><p><strong>Findings:</strong> The proposed model and algorithm are applied to a typical example of SCM problem to illustrate the effectiveness. Based on the sensitivity analysis of the results, the bi-fuzzy nonlinear MODM SCM model is proved to be sensitive to the possibility level ?1.</p><p><strong>Practical implications:</strong> The study focuses on the SCM under complex fuzzy environment in SCM, which has a great practical significance. Therefore, the bi-fuzzy MODM model and MO-APSO can be further applied in SCM problem with quantity discount policy.</p><p><strong>Originality/value:</strong> The bi-fuzzy variable is employed in the nonlinear MODM model of SCM to characterize the hybrid uncertain environment, and this work is original. In addition, the hybrid crisp approach is proposed to transferred to model to an equivalent crisp one by the DMs's degree of optimism and the expected value index. Since the MODM model consider the bi-fuzzy environment and quantity discount policy, so this paper has a great practical significance.</p>http://www.jiem.org/index.php/jiem/article/view/1079bi-fuzzy variable, nonlinear, multi-objective programming, sensitivity analysis, particle swarm optimization |
| spellingShingle | Zhe Zhang Jiuping Xu Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment Journal of Industrial Engineering and Management bi-fuzzy variable, nonlinear, multi-objective programming, sensitivity analysis, particle swarm optimization |
| title | Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment |
| title_full | Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment |
| title_fullStr | Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment |
| title_full_unstemmed | Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment |
| title_short | Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment |
| title_sort | applying nonlinear modm model to supply chain management with quantity discount policy under complex fuzzy environment |
| topic | bi-fuzzy variable, nonlinear, multi-objective programming, sensitivity analysis, particle swarm optimization |
| url | http://www.jiem.org/index.php/jiem/article/view/1079 |
| work_keys_str_mv | AT zhezhang applyingnonlinearmodmmodeltosupplychainmanagementwithquantitydiscountpolicyundercomplexfuzzyenvironment AT jiupingxu applyingnonlinearmodmmodeltosupplychainmanagementwithquantitydiscountpolicyundercomplexfuzzyenvironment |