Replenishment Policy with Deteriorating Raw Material Under a Supply Chain: Complexity and the Use of Ant Colony Optimization

2009 ◽  
pp. 142-152 ◽  
Author(s):  
Jui-Tsung Wong ◽  
Kuei-Hsien Chen ◽  
Chwen-Tzeng Su
Keyword(s):  
Supply Chain ◽  
Ant Colony Optimization ◽  
Ant Colony ◽  
Raw Material ◽  
Replenishment Policy

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

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 ACOCA: Ant Colony Optimization Based Clustering Algorithm for Big Data Preprocessing

2019 ◽  
Vol 4 (5) ◽  
pp. 1239-1250
Author(s):  
Neelam Singh ◽  
Devesh Pratap Singh ◽  
Bhasker Pant
Keyword(s):  
Big Data ◽  
Ant Colony Optimization ◽  
Clustering Algorithm ◽  
Optimization Problems ◽  
Data Preprocessing ◽  
Ant Colony ◽  
Raw Material ◽  
Search Spaces ◽  
Domain Specific Knowledge ◽  
Search Speed

Big Data is rapidly gaining impetus and is attracting a community of researchers and organization from varying sectors due to its tremendous potential. Big Data is considered as a prospective raw material to acquire domain specific knowledge to gain insights related to management, planning, forecasting and security etc. Due to its inherent characteristics like capacity, swiftness, genuineness and diversity Big Data hampers the efficiency and effectiveness of search and leads to optimization problems. In this paper we explore the complexity imposed by big search spaces leading to optimization issues. In order to overcome the above mentioned issues we propose a hybrid algorithm for Big Data preprocessing ACO-clustering algorithm approach. The proposed algorithm can help to increase search speed by optimizing the process. As the proposed method using ant colony optimization with clustering algorithm it will also contribute to reducing pre-processing time and increasing analytical accuracy and efficiency.

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.

scholarly journals SCant-design: Closed loop supply chain design using ant colony optimization

2012 ◽  
Author(s):  
Vasco M.C. Esteves ◽  
Joao M.C. Sousa ◽  
Carlos A. Silva ◽  
Ana P. B. Povoa ◽  
Maria Isabel Gomes
Keyword(s):  
Supply Chain ◽  
Ant Colony Optimization ◽  
Closed Loop ◽  
Ant Colony ◽  
Supply Chain Design ◽  
Closed Loop Supply Chain

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.

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