Comments on “A two-stage supply chain problem with fixed costs: An ant colony optimization approach” by Hong et al. International Journal of Production Economics (2018)

2019 ◽  
Vol 28 (2) ◽  
pp. 183-189
Author(s):  
COSMIN SABO ◽  
ANDREI HORVAT MARC ◽  
PETRICA C. POP
Keyword(s):  
Supply Chain ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Mixed Integer ◽  
Production Economics ◽  
Optimization Approach ◽  
Fixed Costs ◽  
Distribution Centers ◽  
Two Stage ◽  
Chain Problem

The two-stage supply chain problem with fixed costs consists of designing a mimimum distribution cost configuration of the manufacturers, distribution centers and retailers in a distribution network, satisfying the capacity constraints of the manufacturers and distribution centers so as to meet the retailers specific demands. The aim of this work is to pinpoint some inaccuracies regarding the paper entitled ”A two-stage supply chain problem with fixed costs: An ant colony optimization approach” by Hong et al. published in International Journal of Production Economics, Vol. 204, pp. 214–226 (2018) and to propose a valid mixed integer programming based mathematical model of the problem. The comments are related to the mathematical formulation proposed by Hong et al. and the considered test instances.

A two-stage supply chain problem with fixed costs: An ant colony optimization approach

2018 ◽  
Vol 204 ◽  
pp. 214-226 ◽  
Author(s):  
Jiangtao Hong ◽  
Ali Diabat ◽  
Vinay V. Panicker ◽  
Sridharan Rajagopalan
Keyword(s):  
Supply Chain ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Optimization Approach ◽  
Fixed Costs ◽  
Two Stage ◽  
Chain Problem

scholarly journals An Event-Based Supply Chain Partnership Integration Using a Hybrid Particle Swarm Optimization and Ant Colony Optimization Approach

2019 ◽  
Vol 10 (1) ◽  
pp. 190 ◽  
Author(s):  
Zhigang Lu ◽  
Hui Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Supply Chain ◽  
Ant Colony Optimization ◽  
Hybrid Algorithm ◽  
Particle Swarm ◽  
Ant Colony ◽  
Optimization Approach ◽  
Swarm Optimization ◽  
Hybrid Particle Swarm Optimization ◽  
Event Based

Integrating a partnership with potentially stronger suppliers is widely acknowledged as a contributor to the organizational competitiveness of a supply chain. This paper proposes an event-based model which lists the events related with all phases of cooperation with partners and puts events into a dynamic supply chain network in order to understand factors that affect supply chain partnership integration. We develop a multi-objective supply chain partnership integration problem by maximizing trustworthiness, supplier service, qualified products rate and minimizing cost, and then, apply a hybrid algorithm (PSACO) with particle swarm optimization (PSO) and ant colony optimization (ACO) that aims to efficiently solve the problem. It combines the advantages of PSO with reliable global searching capability and ACO with great evolutionary ability and positive feedback. By using the actual data from 1688.com, experimental studies are carried out. The parameter optimizing of the hybrid algorithm is firstly deployed and then we compare the problem solution results of PSACO with the original PSO, ACO. By studying the partnership integration results and implementing analysis of variance (ANOVA) analysis, it shows that the event based model with PSACO approach has validity and superiority over PSO and ACO, and can be served as a tool of decision making for supply chain coordination management in business.

Ant Colony Algorithm for Two Stage Supply Chain

2014 ◽  
pp. 143-155
Author(s):  
R. Sridharan ◽  
Vinay V. Panicker
Keyword(s):  
Supply Chain ◽  
Ant Colony Optimization ◽  
Ant Colony Algorithm ◽  
Transportation Cost ◽  
Allocation Problem ◽  
Ant Colony ◽  
Computational Time ◽  
Fixed Cost ◽  
Two Stage ◽  
Transportation Routes

This chapter focuses on the distribution-allocation problem with fixed cost for transportation routes in a two-stage supply chain. The supply chain considered in this research consists of suppliers, distributors and customers. Each transportation route is associated with a fixed charge (or a fixed cost) and a transportation cost per unit transported. The presence of this fixed cost makes the problem difficult to solve. This motivates the researchers to develop heuristics based on non-traditional optimization techniques that can provide near-optimal solutions in reasonable time. In this research, an ant colony optimization based heuristic is proposed to solve a distribution-allocation problem with fixed cost for transportation routes in a two-stage supply chain. The comparative analysis carried out in this study reveals that the solutions obtained using proposed heuristic are better than those obtained using an existing heuristic in terms of total cost and computational time. In addition, special emphasis is placed in developing heuristics based on ant colony optimization for solving supply chain related problems and identifying opportunities for further research in this area.

scholarly journals An Efficient Hybrid Genetic Approach for Solving the Two-Stage Supply Chain Network Design Problem with Fixed Costs

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 712
Author(s):  
Ovidiu Cosma ◽  
Petrică C. Pop ◽  
Cosmin Sabo
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Fixed Costs ◽  
Distribution Centers ◽  
Two Stage

This paper deals with a complex optimization problem, more specifically the two-stage transportation problem with fixed costs. In our investigated transportation problem, we are modeling a distribution network in a two-stage supply chain. The considered two-stage supply chain includes manufacturers, distribution centers, and customers, and its principal feature is that in addition to the variable transportation costs, we have fixed costs for the opening of the distribution centers, as well as associated with the routes. In this paper, we describe a different approach for solving the problem, which is an effective hybrid genetic algorithm. Our proposed hybrid genetic algorithm is constructed to fit the challenges of the investigated supply chain network design problem, and it is achieved by incorporating a linear programming optimization problem within the framework of a genetic algorithm. Our achieved computational results are compared with the existing solution approaches on a set of 150 benchmark instances from the literature and on a set of 50 new randomly generated instances of larger sizes. The outputs proved that we have developed a very competitive approach as compared to the methods that one can find in the literature.

Distributed supply chain management using ant colony optimization

2009 ◽  
Vol 199 (2) ◽  
pp. 349-358 ◽  
Author(s):  
C.A. Silva ◽  
J.M.C. Sousa ◽  
T.A. Runkler ◽  
J.M.G. Sá da Costa
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Chain Management
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