التفاصيل البيبلوغرافية
| العنوان: |
Two-stage mean-risk stochastic mixed integer optimization model for location-allocation problems under uncertain environment. |
| المؤلفون: |
Liu, Zhimin (AUTHOR) lzmliuzhimin@163.com, Qu, Shaojian (AUTHOR) qushaojian@163.com, Raza, Hassan1 (AUTHOR) hassan_raza783@yahoo.com, Wu, Zhong1 (AUTHOR) wuzhong_bg@usst.edu.cn, Qu, Deqiang1 (AUTHOR) qudeqiang@usst.edu.cn, Du, Jianhui1 (AUTHOR) 1650023854@qq.com |
| المصدر: |
Journal of Industrial & Management Optimization. Sep2021, Vol. 17 Issue 5, p2783-2804. 22p. |
| مصطلحات موضوعية: |
*MATHEMATICAL optimization, *WAREHOUSES, PARTICLE swarm optimization, STOCHASTIC dominance, INTEGERS, GENETIC algorithms |
| مستخلص: |
The problem of the optimal location-allocation of processing factory and distribution center for supply chain networks under uncertain transportation cost and customer demand are studied. We establish a two-stage mean-risk stochastic 0-1 mixed integer optimization model, by considering the uncertainty and the risk measure of the supply chain. Given the complexity of the model this paper proposes a modified hybrid binary particle swarm optimization algorithm (MHB-PSO) to solve the resulting model, yielding the optimal location and maximal expected return of the supply chain simultaneously. A case study of a bread supply chain in Shanghai is then presented to investigate the specific influence of uncertainties on the food factory and distribution center location. Moreover, we compare the MHB-PSO with hybrid particle swarm optimization algorithm and hybrid genetic algorithm, to validate the proposed algorithm based on the computational time and the convergence rate. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Business Source Index |
