In:
Concurrency and Computation: Practice and Experience, Wiley, Vol. 31, No. 10 ( 2019-05-25)
Abstract:
To realize full sharing of mass enterprises in cloud manufacturing environment and free and fair cooperation among the supply chain note‐enterprises, this paper presents a method of combining multi‐Objective Cuckoo Search (MOCS) with Pareto to make optimization of task completion time and cost on supply chain in order to prove the viability and effectiveness of the method, doing the muti‐objective optimization model simulation experiment by MATLAB. The experimental results show that the algorithm performs better than present commonly used multi‐objective optimization genetic algorithm, particle swarm optimization, and artificial fish school algorithm, have better search capability and larger search range, escape from local optimal solution, and achieve the global minimum; the multi‐Objective Cuckoo Search can optimize the combination of supply chain enterprises on cloud manufacturing platform effectively.
Type of Medium:
Online Resource
ISSN:
1532-0626
,
1532-0634
Language:
English
Publisher:
Wiley
Publication Date:
2019
detail.hit.zdb_id:
2052606-4
SSG:
11
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