An Ant Colony Optimization Algorithm for the Redundancy Allocation Problem (RAP)

2004 ◽  
Vol 53 (3) ◽  
pp. 417-423 ◽  
Author(s):  
Y.-C. Liang ◽  
A.E. Smith
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Allocation Problem ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation

ANT COLONY OPTIMIZATION ALGORITHM FOR HETEROGENEOUS REDUNDANCY ALLOCATION IN MULTI-STATE SERIES-PARALLEL SYSTEMS

2009 ◽  
Vol 16 (02) ◽  
pp. 163-186 ◽  
Author(s):  
MANJU AGARWAL ◽  
VIKAS K. SHARMA
Keyword(s):  
System Design ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
System Reliability ◽  
Optimization Problems ◽  
Ant Colony ◽  
System Structure ◽  
Ant Colony Optimization Algorithm ◽  
Redundancy Allocation ◽  
Demand Distribution

This paper addresses the redundancy allocation problem of multi-state series-parallel reliability structures where each subsystem can consist of maximum two types of redundant components. The objective is to minimize the total investment cost of system design satisfying system reliability constraint and the consumer load demand. The demand distribution is presented as a piecewise cumulative load curve. The configuration uses the binary components from a list of available products to provide redundancy so as to increase system reliability. The components are characterized by their feeding capacity, reliability and cost. A system that consists of elements with different reliability and productivity parameters has the capacity strongly dependent upon the selection of components constituting its structure. An ant colony optimization algorithm has been presented to analyze the problem and suggest an optimal system structure. The solution approach consists of a series of simple steps as used in early ant colony optimization algorithms dealing with other optimization problems and still proves efficient over the prevalent methods with regard to solutions obtained/computation time. Three multi-state system design problems have been solved for illustration.

Modeling and optimizing logistics, information, economic and financial intercluster cooperation using the ant colony optimization algorithm

2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Population Decline ◽  
Innovation System ◽  
Federal District ◽  
Original Model ◽  
Ant Colony ◽  
Industrial Agglomeration ◽  
Ant Colony Optimization Algorithm

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.

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