Multi-Objective Genetic Algorithms for the Single Allocation Hub Location Problem


Autoria(s): Asobiela, Stephen Yamzuuga
Contribuinte(s)

Department of Computer Science

Data(s)

12/09/2013

12/09/2013

12/09/2013

Resumo

Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.

Identificador

http://hdl.handle.net/10464/4985

Idioma(s)

eng

Publicador

Brock University

Palavras-Chave #Genetic Algorithms, Multi-Objective, Pareto Ranking, Sum of Ranks, Hub Location Problem, Weighted Sum
Tipo

Electronic Thesis or Dissertation