Kanya Auckara-aree and Rein Boondiskulchok

pp. 581 - 588

Abstract

In this study, we investigate a complex situation in designing a raw material collection system, which involves collection station location, supplier selection, supplier–collection allocation, and transporation decisions. In a raw material collection
system, a collector has to collect more raw material quantity in order to get higher income as the price of raw material is
quantity dependent. The more suppliers visit, the more income receives; however, when a collector decides to visit more
suppliers, traveling distance will be longer, which will result in higher transportation costs. We formulate a Mixed Integer
Programming for a location routing with setp–price policy model to find the optimal solution. The basic trade–off of the
proposed model is between revenue received from totally collected quantity and total costs both fixed costs and variable
costs from expanding the collection area. Instances which are created according to real–life data are applied to test the
proposed model. The computational results indicate that the complex raw material collcetion system can be obtained by the
proposed mathethical model. The mathematical model gives the benefit for the use of determining the optimum raw material
collection system with profit maximization. The results can be used for setting up a real raw material collection system.