Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment

Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment

This paper studies a supply chain network design model with price competition. The supply chain provides multiple products for a market area in multiple periods. The model considers the location of manufacturers and retailers and assumes a probabilistic customer behavior based on an attraction funct...

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Main Authors: Jian Wang, Xueyan Wang, Mingzhu Yu
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/8548150
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spelling doaj-0f05b4281d284515972e3682d8534a152020-11-25T01:49:02ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/85481508548150Multi-Period Multi-Product Supply Chain Network Design in the Competitive EnvironmentJian Wang0Xueyan Wang1Mingzhu Yu2School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430074, ChinaSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430074, ChinaInstitute of Big Data Intelligent Management and Decision, College of Management, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, ChinaThis paper studies a supply chain network design model with price competition. The supply chain provides multiple products for a market area in multiple periods. The model considers the location of manufacturers and retailers and assumes a probabilistic customer behavior based on an attraction function depending on both the location and the quality of the retailers. We aim to design the supply chain under the capacity constraint and maximize the supply chain profit in the competitive environment. The problem is formulated as a mixed integer nonlinear programming model. To solve the problem, we propose two heuristic algorithms—Simulated Annealing Search (SA) and Particle Swarm Optimization (PSO)—and numerically demonstrate the effectiveness of the proposed algorithms. Through the sensitivity analysis, we give some management insights.http://dx.doi.org/10.1155/2020/8548150
collection DOAJ
language English
format Article
sources DOAJ
author Jian Wang
Xueyan Wang
Mingzhu Yu
spellingShingle Jian Wang
Xueyan Wang
Mingzhu Yu
Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment
Mathematical Problems in Engineering
author_facet Jian Wang
Xueyan Wang
Mingzhu Yu
author_sort Jian Wang
title Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment
title_short Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment
title_full Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment
title_fullStr Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment
title_full_unstemmed Multi-Period Multi-Product Supply Chain Network Design in the Competitive Environment
title_sort multi-period multi-product supply chain network design in the competitive environment
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description This paper studies a supply chain network design model with price competition. The supply chain provides multiple products for a market area in multiple periods. The model considers the location of manufacturers and retailers and assumes a probabilistic customer behavior based on an attraction function depending on both the location and the quality of the retailers. We aim to design the supply chain under the capacity constraint and maximize the supply chain profit in the competitive environment. The problem is formulated as a mixed integer nonlinear programming model. To solve the problem, we propose two heuristic algorithms—Simulated Annealing Search (SA) and Particle Swarm Optimization (PSO)—and numerically demonstrate the effectiveness of the proposed algorithms. Through the sensitivity analysis, we give some management insights.
url http://dx.doi.org/10.1155/2020/8548150
work_keys_str_mv AT jianwang multiperiodmultiproductsupplychainnetworkdesigninthecompetitiveenvironment
AT xueyanwang multiperiodmultiproductsupplychainnetworkdesigninthecompetitiveenvironment
AT mingzhuyu multiperiodmultiproductsupplychainnetworkdesigninthecompetitiveenvironment
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