A decision-making technique for solving order allocation problem using a genetic algorithm

被引:16
作者
Ahmad, Ijaz [1 ]
Liu, Yan [1 ]
Javeed, Danish [1 ]
Ahmad, Shahab [2 ]
机构
[1] Changchun Univ Sci & Technol, Sch Comp Sci & Technol, Changchun 130022, Peoples R China
[2] Chongqing Univ Post & Telecommun, Sch Econ & Management, Chongqing 400065, Peoples R China
来源
2020 6TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, CONTROL AND ROBOTICS (EECR 2020) | 2020年 / 853卷
关键词
Genetic Algorithm; Multi-objective; Order crossover; Simulated Binary Crossover; GREEN SUPPLIER SELECTION; PROGRAMMING APPROACH; SUPPORT-SYSTEM; MODEL; CHAIN;
D O I
10.1088/1757-899X/853/1/012054
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The selection of proper suppliers is one of the most complicated works of the purchasing department. Today, supplier selection includes different conflicting objectives. Because of contradictory multi-objective supplier selection is solving by using the decision-making technique. This paper is presented a modified genetic algorithm by using a combination of crossover operators, Order crossover (OX), Simulated binary crossover (SBX) to assign the optimal order quantities to each supplier, with criteria of transportation cost, product quality, and delivery time with a quantity discount. The result shows that the modified genetic algorithm is an allocated optimal order for multi vendors with improves quality as well as less computational times.
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页数:9
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