This research aims to explore PPVRP, which comprises two optimisation problems: packing problem, and routing problem. The packing problem takes into account the positive and negative alignments of distributing several items (e.g. fragile or chemical items) together. Examples may be found in grocery and pharmaceutical industry. The routing problem is about finding the optimal vehicle route given time window constraints and limited number of vehicles. Furthermore, the demand of customers and the capabilities of each vehicle must be respected. We will develop a model to integrate the two problems into a general mixed integer linear programming. The expected result is to be able to maximize total profit of all the selected items from all trips. The model will be solved by two stage decomposition methods, which includes: packing problem formulated as quadratic knapsack problem and routing problem formulated as multi constraints knapsack problem. This is, to the best of our knowledge, the first time the PPVRP model has been considered as two stage decomposition model with the packing problem being quadratic knapsack problem.
Ponpot Jartnillaphand is currently a third-year student at Curtin University. Before he came to Australia, he studied his first and second year at Mahidol University in Thailand. His study focuses specifically on Industrial Optimization as his major course and Data Science as his minor course. He is interested in doing research and hope to submit it for a journal publication. In the unit “industrial project” in his third year, he has already improved the classic model of Quadratic Knapsack Problem for packing problem and solved the model by using many solution methods.