Archives > Volume 16 | Number 1 | March 2021 > pp 112–124
Advances in Production Engineering & Management
Volume 16 | Number 1 | March 2021 | pp 112–124
Optimization of a multi-objective location model of manufacturing base considering cooperative manufacturing capabilities and service benefits
Sun, J.Z.; Zhang, Q.S.; Yu, Y.Y.
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A B S T R A C T
Improving customer satisfaction and shortening the manufacturing cycle have become common concerns of current manufacturers. This paper presents a multi-objective location model considering the maximization of collaborative manufacturing capabilities and service benefits. This method first uses the two dimensions of customer share and market consumption to segment customers, and identify the weight of various customer groups. Secondly, the space vector model (VSM) is used to calculate the matching between manufacturing capabilities and manufacturing requirements. Then build a multi-objective location model based on the two goals of collaborative manufacturing capabilities and service benefits. Finally, the model was tested with simulation data, which proved the validity and feasibility of the model. According to the simulation results, managers can accurately select the optimal manufacturing base from multiple candidate manufacturing bases with regard to less costs, shorter lead times, better manufacturing capabilities, better service benefits. In this paper, Fuzzy theory, Logit model and VSM are combined to salve the problem of manufacturing base location. Considering resources and service benefits of each manufacturing base, it is helpful to optimize the location of enterprises. From the academic and practical points, this study provides a new perspective for the location problem.
A R T I C L E I N F O
Keywords • Manufacturing base; Location model; Multi-objective model; Optimization; Decision-making; Customer demand preference; Collaborative manufacturing
Corresponding author • Sun, J.Z.
Article history • Received 2 February 2021, Revised 22 February 2021, Accepted 28 February 2021
Published on-line • 26 March 2021
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