Block transportation scheduling under delivery restriction in shipyard using meta-heuristic algorithms

• We consider a scheduling problem of block transportation under delivery restriction.
• We derive a mathematical model to minimize the penalty times that can cause delays in the overall block production schedule.
• We propose two meta-heuristic algorithms based on genetic algorithm (GA) and self-evolution algorithm (SEA).
• We evaluate the performances of the GA and SEA using several randomly generated examples.

Special vehicles called transporters are used to deliver heavy blocks from one plant to another in shipyards. Because of the limitation on the number of transporters, the scheduling of transporters is important for maintaining the overall production schedule of the blocks. This paper considers a scheduling problem of block transportation under a delivery restriction to determine when and by which transporter each block is delivered from its source plant to its destination plant. The objective of the problem is to minimize the penalty times that can cause delays in the overall block production schedule. A mathematical model for the optimal solution is derived, and two meta-heuristic algorithms based on a genetic algorithm (GA) and a self-evolution algorithm (SEA) are proposed. The performance of the algorithms is evaluated with several randomly generated experimental examples.