Quantum Harmony Search Algorithm for Assembly Sequence Planning of Design Knowledge Resources in the Cloud Manufacturing Environment

Abstract:

Facing the condition of scattered and disorder design knowledge and insufficient innovative capacity of Small and Medium Enterprises (SMEs) in Cloud Manufacturing environment, making for the design of knowledge assembled into orderly combination of knowledge resources, this paper presents the service capacity of evaluation model of knowledge resources and programming knowledge resources in the assembly sequence the mathematical model of the planning and design to solve the model of quantum harmony search algorithm (QHS). QHS algorithm bases on the Latin hypercube (LH), and improves the global search capability through the introduction of quantum coding and quantum gate transformation. Taking mold design knowledge of SMEs resources planning issues as example, according to the mathematical model, QHS algorithm aims to solve the knowledge resources assembly sequence of the optimal design in the cost and quality constraints, and verifies the feasibility and practicality of the method. This paper has practical significance to improve the overall SMEs innovation and design capabilities and make the reuse of the design knowledge more efficiency in the Cloud Manufacturing environment.

• Periodical: Advanced Materials Research (Volumes 774-776)
• Pages: 1386-1392
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.774-776.1386
• Online since: September 2013
• Authors: Lei Wang, Yu Cheng Lin, Wei Guo, Nan Zhao
• Keywords: Cloud Manufacturing, Design Knowledge Assembly, Quantum Harmony Search, Sequence Planning, Service Capacity Assessment

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