Solving Service Selection Problem Based on a Novel Multi-Objective Artificial Bees Colony Algorithm

doi:10.1007/s12204-017-1860-2

Abstract

Abstract: Abstract: Service computing is a new paradigm and has been widely used in many fields. The multi-objective service selection is a basic problem in service computing and it is non-deterministic polynomial (NP)-hard. This paper proposes a novel multi-objective artificial bees colony (n-MOABC) algorithm to solve service selection problem. A composite service instance is a food source in the algorithm. The fitness of a food source is related to the quality of service (QoS) attributes of a composite service instance. The search strategy of the bees are based on dominance. If a food source has not been updated in successive maximum trial (Max Trial) times, it will be abandoned. In experiment phase, a parallel approach is used based on map-reduce framework for n-MOABC algorithm. The performance of the algorithm has been tested on a variety of data sets. The computational results demonstrate the effectiveness of our approach in comparison to a novel bi-ant colony optimization (NBACO) algorithm and co-evolution algorithm.

Key words: novel multi-objective artificial bees colony (n-MOABC)| multi-objective| service selection| search strategy

摘要： Abstract: Service computing is a new paradigm and has been widely used in many fields. The multi-objective service selection is a basic problem in service computing and it is non-deterministic polynomial (NP)-hard. This paper proposes a novel multi-objective artificial bees colony (n-MOABC) algorithm to solve service selection problem. A composite service instance is a food source in the algorithm. The fitness of a food source is related to the quality of service (QoS) attributes of a composite service instance. The search strategy of the bees are based on dominance. If a food source has not been updated in successive maximum trial (Max Trial) times, it will be abandoned. In experiment phase, a parallel approach is used based on map-reduce framework for n-MOABC algorithm. The performance of the algorithm has been tested on a variety of data sets. The computational results demonstrate the effectiveness of our approach in comparison to a novel bi-ant colony optimization (NBACO) algorithm and co-evolution algorithm.

关键词: novel multi-objective artificial bees colony (n-MOABC)| multi-objective| service selection| search strategy

CLC Number:

TP 301.6

HUANG Liping1,2* (黄丽萍), ZHANG Bin2 (张斌), YUAN Xun3 (苑勋),ZHANG Changsheng2 (张长胜), GAO Yan2 (高岩). Solving Service Selection Problem Based on a Novel Multi-Objective Artificial Bees Colony Algorithm[J]. Journal of shanghai Jiaotong University (Science), 2017, 22(4): 474-480.

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