Abstract:
This research addresses a real–life problem which aims to maximize profit of raw material collection system in the natural rubber industry. To establish the collection system, the system investigated in this research is concerned with not only location decision, allocation decision, and routing decision, but also with supplier selection decision with influence of step–price policy. Step–price policy sets by the factory give incentive to collector to collect as large quantity as possible of natural rubber from suppliers in order to receive a higher price for raw material. It is essential to find the set of suppliers included in the system. In addition, other conditions such as vehicle capacity and biological time duration are also considered. The main objective of this research is to find the optimal set of suppliers so that the profit of the collection system is maximized. The location allocation and vehicle routing with step–price policy is formulated as a Mixed Integer Programming model (MIP). With lots of complexities present in the problem, a heuristic method consisting of three stages is developed. The location allocation stage constructs one feasible solution while the routing improvement is then applied in order to reduce total system cost. The supplier screening stage is lastly added to find other potential sets of suppliers who can generate better profit. Computational test results are analyzed and discussed based on both performance and solving time. The comparison of the results shows that the solution of the heuristic solution method is slightly different from the mathematical model solution of which a less than 15.7% average difference is recorded. Meanwhile, computational time is saved more than 99.8% of average difference.
