Reducing simulation costs of embedded simulation in yard crane dispatching in container terminals

Abstract

Embedding simulation in optimization algorithms will incur computational costs. For NP-hard problems the computational costs of the embedded simulation in the optimization algorithm are likely to be substantial. YC dispatching is NP-hard. So it is very important to be able to minimize simulation costs in YC dispatching algorithms. In the optimization algorithm for yard crane dispatching published, simulation of YC operations of the entire (partial) sequence of YC jobs are carried out each time the tardiness of a (partial) sequence needs to be evaluated. In this paper we study two approaches to reduce simulation costs in these embedded simulations in the optimization algorithm. Experimental results show that one approach significantly reduces the computational time of the optimization algorithm. We also analyze the reasons for the other approach which fails to reduce the computational time.

Improving Computational Performance of Simulation-based Heuristic Algorithms for Job Sequencing

“…In many algorithms, substantial amount of time is required in the simulation experiments to evaluate the solutions to the problem. When a candidate solution is built incrementally in an optimization algorithm for deterministic problems, two methods to reduce simulation cost by incremental evaluation are investigated in [1]. A TREE data structure is used to save the performance of solutions and system status.…”