Open AccessA decision-making technique for solving order allocation problem using a genetic algorithm
Author(s) -
Ijaz Ahmad,
Yan Liu,
Danish Javeed,
Shahab Ahmad
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/853/1/012054
Subject(s) - crossover , selection (genetic algorithm) , genetic algorithm , purchasing , computer science , mathematical optimization , order (exchange) , quality (philosophy) , binary number , operations research , product (mathematics) , algorithm , mathematics , artificial intelligence , operations management , engineering , economics , philosophy , geometry , arithmetic , finance , epistemology
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 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.