Network design problem with relays: A genetic algorithm with a path-based crossover and a set covering formulation

► A new formulation to the network design problems with relays is developed. ► The problem is separated into two distinct problems as the path and relay problems. ► A genetic algorithm is used to solve the path problem. ► The relay problem is formulated and solved as a set covering problem. ► The pr...

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Bibliographic Details
Published in:European journal of operational research Vol. 218; no. 3; pp. 829 - 837
Main Author: Konak, Abdullah
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.05.2012
Elsevier
Elsevier Sequoia S.A
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ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:► A new formulation to the network design problems with relays is developed. ► The problem is separated into two distinct problems as the path and relay problems. ► A genetic algorithm is used to solve the path problem. ► The relay problem is formulated and solved as a set covering problem. ► The proposed approach outperforms previous approaches. The network design problem with relays arises in telecommunications and distribution systems where the payload must be reprocessed at intermediate stations called relays on the route from its origin to its destination. In fiber-optic networks, for example, optical signals may be regenerated several times to overcome signal degradation because of attenuation and other factors. Given a network and a set of commodities, the network design problem with relays involves selecting network edges, determining a route for each commodity, and locating relays to minimize the network design cost. This paper presents a new formulation to the problem based on set covering constraints. The new formulation is used to design a genetic algorithm with a specialized crossover/mutation operator which generates a feasible path for each commodity, and the locations of relays on these paths are determined by solving the corresponding set covering problem. Computational experiments show that the proposed approach can outperform other approaches, particularly on large size problems.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2011.11.046