Two effective metaheuristic algorithms for solving a stochastic optimization model of a multi-echelon supply chain-Reference-Cited by-同舟云学术

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Two effective metaheuristic algorithms for solving a stochastic optimization model of a multi-echelon supply chain

Published:2019-03 Issue: Volume:76 Page:545-563
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Khalifehzadeh Sasan^ORCID,Fakhrzad M.B.^ORCID,Zare Mehrjerdi Yahia,Hosseini_Nasab Hasan

Publisher

Elsevier BV

Subject

Software

Reference61 articles.

1. A two-stage stochastic programming approach for new tape-out allocation decisions for demand fulfillment planning in semiconductor manufacturing;Chien;Flex. Serv. Manuf. J.,2013

2. Chance constraint-based multi-objective stochastic model for supplier selection;Aggarwal;Int. J. Adv. Manuf. Technol.,2015

3. A genetic algorithm approach for multi-objective optimization of supply chain networks;Altiparmak;Comput. Ind. Eng.,2006

4. An extended state task network formulation for integrated production-distribution planning in supply chain;Su;Int. J. Adv. Manuf. Technol.,2008

5. A dynamic model for facility location in the design of complex supply chains;Thanh;Int. J. Prod. Econ.,2008

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1. Integrating the Scheduling, Due Date Quotation, and Pricing in Dual-Channel Supply Chain with a Two-Stage Stochastic Approach and Dynamic Pricing Scheme;2024

2. Multi-supplier, multi-objective supply chain cost-optimization model;Research in Mathematics;2023-08-20

3. On the Integration of Google Cloud and SAP HANA for Adaptive Supply Chain in Retailing;Procedia Computer Science;2023

4. A fuzzy based multiobjective optimization of multi echelon supply chain network;Journal of Intelligent & Fuzzy Systems;2020-10-07

5. A multi-objective pharmaceutical supply chain network based on a robust fuzzy model: A comparison of meta-heuristics;Applied Soft Computing;2020-07

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