Multi-objective demand fulfillment problem for solar cell industry

ASIAIR > College of Management > Department of Business Administration > Journal Article > Item 310904400/111598

Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/111598

Title:	Multi-objective demand fulfillment problem for solar cell industry
Authors:	鄭家年;Zheng, Jia-Nian;*;簡禎富;Chien, Chen-Fu;吳吉政;Wu, Jei-Zheng
Contributors:	經營管理學系
Date:	2018-05
Issue Date:	2018-10-22 03:44:09 (UTC+0)
Abstract:	With the growth of green energy market, there are many companies with vertical integration and outsourcing process. Their business models in the solar cell industry cause different influence on the business objectives including revenue, profit, and gross margin. The sales managers are hard to generate fast and reliable ATP (Available-to-promise) which covered all business objectives. Under the various products types with limited quantity, the loading of factory is uncertain and the quantity of order becomes huger. This study formulates multi-objective demand fulfillment problem in solar cell industry and applies a multi-objective genetic algorithm (moGA) to optimize the ATP. The model trade-offs objectives with by Pareto approach without sacrificing other benefits. The multi-population strategy used for stability of solutions. Results of empirical study show that the proposed moGA can improve gross margin while maintaining the desired revenue and profit. With effective solutions and reasonable computing time, the decision support system with proposed moGA has become a regular communication bridge between sales and production departments in the case company. Graphical abstract The yellow triangle is the best solution and the red square is other suggested solutions which in Pareto set; the green diamonds is searched solutions which were not in front-end set (not suggested).
Relation:	COMPUTERS & INDUSTRIAL ENGINEERING
Appears in Collections:	[Department of Business Administration] Journal Article

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