A Novel Service Composition Algorithm for Cloud-Based Manufacturing Environment

Abstract

Cloud Manufacturing Service Composition (CMSC) is the key issue and taking an important role in solving the interconnection and interoperability of resources and services for Cloud Manufacturing (CMfg). CMSC is a typical kind of NP-hard problems with the characteristics of dynamic and uncertainty. Solving large scale CMSC problem by using the traditional methods might be not efficient because of the massive complex resources and large-scale searching space. To overcome this shortcoming, a novel artificial bee colony algorithm named Multiple Improvement Strategies based Artificial Bee Colony algorithm (MISABC) is proposed. MISABC improves the performance of classical ABC algorithm through several strategies such as (a) differential evolution strategy (DES), (b) oscillation strategy with classical trigonometric factor (TFOS), (c) different dimensional variation learning strategy (DDVLS), (d) Gaussian distribution strategy (GDS). Meanwhile, to address the CMfg scenario, we also propose a manufacturing service composition scheme named as Multi-Module Subtasks Collaborative Execution for Cloud Manufacturing Service Composition (MMSCE-CMSC). Eight benchmark functions with different characteristics, a comparison study with existed improved ABC algorithms and a case study are used to validate the performance of the algorithm. The results demonstrate the effectiveness of the proposed method for addressing complex CMSC problem in CMfg.

Keywords

• Cloud manufacturing
• cloud manufacturing service composition
• multi-module subtasks
• artificial bee colony algorithm