Open AccessUtilization of Genetic Algorithm in Allocating Goods to Shop Shelves
Author(s) -
Kazuhiro Takeyasu,
Yuki Higuchi
Publication year - 2016
Publication title -
business and management research
Language(s) - English
Resource type - Journals
eISSN - 1927-601X
pISSN - 1927-6001
DOI - 10.5430/bmr.v5n4p1
Subject(s) - genetic algorithm , computer science , position (finance) , operations research , mathematical optimization , integer (computer science) , integer programming , economics , algorithm , mathematics , finance , programming language
How to allocate goods in shop shelves makes great influence to sales amount. Searching best fit allocation of goods to shelves is a kind of combinatorial problem. This becomes a problem of integer programming and utilizing genetic algorithm may be an effective method. Reviewing past researches, there are few researches made on this. Formerly, we have presented a papers concerning optimization in allocating goods to shop shelves utilizing genetic algorithm. In those papers, the problem that goods were not allowed to allocate in multiple shelves and the problem that goods were allowed to allocate in multiple shelves were pursued. In this paper, we examine the problem that allows goods to be allocated in multiple shelves and introduce the concept of sales profits and sales probabilities. Expansion of shelf position is executed. Optimization in allocating goods to shop shelves is investigated. Utilizing genetic algorithm, optimum solution is pursued and verified by a numerical example. Various patterns of problems must be examined hereafter.