Abstract
Web service location allocation problem is an important problem in the modern IT industry. In this paper, the two major objectives, i.e. deployment cost and network latency, are considered simultaneously. In order to solve this new multi-objective problem effectively, we adopted the framework of binary Particle Swarm Optimization (PSO) due to its efficacy that has been demonstrated in many optimization problems. Specifically, we developed two PSO variants, one with weighted-sum fitness function (WSPSO) and the other with dominance-based fitness function. Concretely, it uses the fast Non-dominate Sorting scheme, and thus is called NSPSO. The experimental results showed that both PSO variants performed better than NSGA-II, which is the one of the most commonly used multi-objective genetic algorithms. Furthermore, we have found that NSPSO achieved a more diverse set of solutions than WSPSO, and thus covers the Pareto front better. This demonstrates the efficacy of using the dominance-based fitness function in solving multi-objective Web service location allocation problem.
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Tan, B., Mei, Y., Ma, H., Zhang, M. (2016). Particle Swarm Optimization for Multi-Objective Web Service Location Allocation. In: Chicano, F., Hu, B., García-Sánchez, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2016. Lecture Notes in Computer Science(), vol 9595. Springer, Cham. https://doi.org/10.1007/978-3-319-30698-8_15
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DOI: https://doi.org/10.1007/978-3-319-30698-8_15
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