Ship Inventory Routing and Scheduling
This research investigates a ship inventory routing and scheduling problem with undedicated compartments (sIRPSP-UC). The objective of the problem is to find a minimum cost solution while satisfying a number of technical and physical constraints within a given planning horizon. In this problem, we identify four subproblems that need to be decided simultaneously: route selections, ship selection, loading, and unloading activity procedures. First, we (Siswanto, Essam and Sarker) develop an equivalent mixed integer linear programming of the problem. Then, we propose a set of heuristics for each sub-problem and find the best combination of heuristics that ensures an overall best solution for the entire problem.
In 2011, we considered a new variant of the maritime inventory routing problem which involved multiple time windows, and is hence called the multiple time windows problem. We have developed a mathematical model for this problem. However, due to the excessive running time required for the mathematical model, we have also developed a multi-heuristics based genetic algorithm. The multi-heuristics are composed of a set of strategies that correspond to the above four decision points. We used this set of strategies in a genetic algorithm framework so as to find the best strategies. The computational results show that the multi-heuristics can get acceptable solutions within a reasonable running time. Moreover, the flexibility to add or remove the strategies means that the proposed method would not be difficult to implement for other variants of the maritime inventory routing problem. From this research, a paper has been published in Computers and Industrial Engineering in 2011.