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.

Ant Colony Algorithm for Single Stage Supply Chain

2014 ◽  
pp. 131-142
Author(s):  
R. Sridharan ◽  
Vinay V. Panicker
Keyword(s):  
Supply Chain ◽  
Ant Colony Optimization ◽  
Swarm Intelligence ◽  
Ant Colony Algorithm ◽  
Optimization Problems ◽  
Allocation Problem ◽  
Single Stage ◽  
Ant Colony ◽  
Fixed Cost ◽  
Modeling And Analysis

Swarm intelligence has emerged as an approach for developing meta-heuristics to solve combinatorial optimization problems. Ant Colony Optimization (ACO) is an example for a swarm-intelligence based meta-heuristic inspired by the social behavior of colonies of ants. In this chapter, an ACO-based heuristic is proposed for solving a distribution-allocation problem in a single-stage of a supply chain. Thus, this work aims at modeling and analysis of the distribution-allocation problem in a single-stage supply chain with a fixed cost for a transportation route. In addition, it provides an insight for researchers in developing heuristics based on ant colony optimization for supply chain related problems.

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

A flexibility method for structural damage identification using continuous ant colony optimization

2015 ◽  
Vol 11 (2) ◽  
pp. 186-201 ◽  
Author(s):  
Maryam Daei ◽  
S. Hamid Mirmohammadi
Keyword(s):  
Experimental Data ◽  
Damage Detection ◽  
Ant Colony Optimization ◽  
Structural Damage ◽  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Computational Time ◽  
Content Type ◽  
Flexibility Matrix

Purpose – The interest in the ability to detect damage at the earliest possible stage is pervasive throughout the civil engineering over the last two decades. In general, the experimental techniques for damage detection are expensive and require that the vicinity of the damage is known and readily accessible; therefore several methods intend to detect damage based on numerical model and by means of minimum experimental data about dynamic properties or response of damaged structures. The paper aims to discuss these issues. Design/methodology/approach – In this paper, the damage detection problem is formulated as an optimization problem such as to obtain the minimum difference between the numerical and experimental variables, and then a modified ant colony optimization (ACO) algorithm is proposed for solving this optimization problem. In the proposed algorithm, the structural damage is detected by using dynamically measured flexibility matrix, since the flexibility matrix of the structure can be estimated from only the first few modes. The continuous version of ACO is employed as a probabilistic technique for solving this computational problem. Findings – Compared to classical methods, one of the main strengths of this meta-heuristic method is the generally better robustness in achieving global optimum. The efficiency of the proposed algorithm is illustrated by numerical examples. The proposed method enables the deduction of the extent and location of structural damage, while using short computational time and resulting good accuracy. Originality/value – Finding accurate results by means of minimum experimental data, while using short computational time is the final goal of all researches in the structural damage detection methods. In this paper, it gains by applying flexibility matrix in the definition of objective function, and also via using continuous ant colony algorithm as a powerful meta-heuristic techniques in the constrained nonlinear optimization problem.

A Hierarchical Approach to the Capacitated Single Allocation p-Hub Median Problem with Direct Shipment

2012 ◽  
Vol 209-211 ◽  
pp. 807-813
Author(s):  
Ji Ung Sun ◽  
Don Ki Baek
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Optimal Solution ◽  
Ant Colony ◽  
Network Design Problem ◽  
Computational Time ◽  
Fixed Cost ◽  
Ant Colony Optimization Algorithm ◽  
Median Problem ◽  
Single Allocation

In this paper we consider a capacitated single allocation p-hub median problem with direct shipment (CSApHMPwD). We determine the location of p hubs, the allocation of non-hub nodes to hubs, and direct shipment paths in the network. This problem is formulated as 0-1 integer programming model with the objective of the minimum total transportation cost and the fixed cost associated with the establishment of hubs. An optimal solution is found using CPLEX for the small sized problems. Since the CSApHMPwD is NP-hard, it is difficult to obtain optimal solution within a reasonable computational time. Therefore, an ant colony optimization algorithm is developed which solves hub selection and node allocation problem hierarchically. Its performance is examined through a comparative study. The experimental results show that the proposed ant colony optimization algorithm can be a viable solution method for the capacitated hub and spoke network design problem.

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.

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 Nelder and Mead Methodology for Solving Small Fixed-Charge Transportation Problems

2011 ◽  
pp. 345-356
Author(s):  
G. Kannan ◽  
P. Senthil ◽  
P. Sasikumar ◽  
V. P. Vinay
Keyword(s):  
Supply Chain ◽  
Transportation Problem ◽  
Optimization Problems ◽  
Fixed Charge ◽  
Computational Time ◽  
Variable Cost ◽  
Fixed Cost ◽  
Supply Chain Optimization ◽  
Business World ◽  
Fixed Charge Transportation Problem

The term ‘supply chain management’ has become common in the business world, which can be understood from the positive results of research in the area, particularly in supply chain optimization. Transportation is a frontier in achieving the objectives of the supply chain. Thrust is also given to optimization problems in transportation. The fixed-charge transportation problem is an extension of the transportation problem that includes a fixed cost, along with a variable cost that is proportional to the amount shipped. This article approaches the problem with another meta-heuristics known as the Nelder and Mead methodology to save the computational time with little iteration and obtain better results with the help of a program in C++.

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