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 t2he concept of sales profits and sales
probabilities. Expansion of shelf is executed. Optimization in allocating goods
to shop shelves is investigated. An application to the convenience store with
POS sales data of cup noodles is executed. Utilizing genetic algorithm, optimum
solution is pursued and verified by a numerical example. Various patterns of problems must be