Near optimal process plan selection for multiple jobs in networked based manufacturing using multi-objective evolutionary algorithms

Authors:
V. K. Manupati;J. J. Thakkar;K. Y. Wong;M. K. Tiwari
Affiliations:
Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur 721 302, West Bengal, India;Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur 721 302, West Bengal, India;Department of Manufacturing and Industrial Engineering, Universiti Teknologi Malaysia, Skudai, Malaysia;Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur 721 302, West Bengal, India
Venue:
Computers and Industrial Engineering
Year:
2013

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Abstract

The networked manufacturing offers several advantages in current competitive atmosphere by way of reducing the manufacturing cycle time and maintenance of the production flexibility, thereby achieving several feasible process plans. In this paper, we have addressed a Multi Objective Problem (MOP) which covers-minimize the makespan and to maximize the machine utilization while generating the feasible process plans for multiple jobs in the context of network based manufacturing system. A new multi-objective based Territory Defining Evolutionary Algorithm (TDEA) to resolve the above computationally challenge problem have been developed. In particular, with two powerful Multi-Objective Evolutionary Algorithms (MOEAs), viz. Non-dominated Sorting Genetic Algorithm (NSGA-II) and Controlled Elitist-NSGA-II (CE-NSGA-II) the performance of the proposed TDEA has been compared. An illustrative example along with three complex scenarios is presented to demonstrate the feasibility of the approach. The proposed algorithm is validated and the results are analyzed and compared.