On the effects of seeding strategies: A case for search-based multi-objective service composition

Chen，Tao1,2; Li，Miqing2; Yao，Xin2,3

10.1145/3205455.3205513

2018-07-02

GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference

1419-1426

Kyoto, Japan

Association for Computing Machinery, Inc

Service composition aims to search a composition plan of candidate services that produces the optimal results with respect to multiple and possibly conflicting Quality-of-Service (QoS) attributes, e.g., latency, throughput and cost. This leads to a multi-objective optimization problem for which evolutionary algorithm is a promising solution. In this paper, we investigate different ways of injecting knowledge about the problem into the Multi-Objective Evolutionary Algorithm (MOEA) by seeding. Specifically, we propose four alternative seeding strategies to strengthen the quality of the initial population for the MOEA to start working with. By using the real-world WS-DREAM dataset, we conduced experimental evaluations based on 9 different workflows of service composition problems and several metrics. The results confirm the effectiveness and efficiency of those seeding strategies. We also observed that, unlike the discoveries for other problem domains, the implication of the number of seeds on the service composition problems is minimal, for which we investigated and discussed the possible reasons.

Evolutionary algorithm Multiobjective optimization Search-based software engineering Seeding strategy Service composition

其他

英语

EI ; CPCI-S

20183105630287

Multiobjective optimization ; Quality of service ; Software engineering

Computer Programming:723.1 ; Optimization Techniques:921.5

2-s2.0-85050635752

Scopus

1.Department of Computing and Technology, Nottingham Trent University, ,United Kingdom
2.CERCIA, School of Computer Science, University of Birmingham, ,United Kingdom
3.Department of Computer Science and Engineering, Southern University of Science and Technology, ,China

Chen，Tao,Li，Miqing,Yao，Xin. On the effects of seeding strategies: A case for search-based multi-objective service composition[C]:Association for Computing Machinery, Inc,2018:1419-1426.