Scheduling Yard Cranes in a Container Terminal Using a New Genetic Approach

Effective and efficient scheduling of yard crane operations is essential to guarantee a smooth and fast container flow in a container terminal, thus leading to a high terminal throughput. This paper studies the problem of scheduling yard cranes to perform a given set of loading and unloading jobs with different ready times in a yard zone. In particular, the inter-crane interference between adjacent yard cranes which results in the movement of a yard crane being blocked by adjacent yard cranes is studied. The objective is to minimize the sum of yard crane completing times. Since the scheduling problem is NP-complete, a new hybrid optimization algorithm combining the techniques of genetic algorithm and tabu search method (GA-TS) is proposed to solve the challenging problem. Two new operators, namely the Tabu Search Crossover (TSC) and the Tabu Search Mutation (TSM), are introduced into the proposed algorithm to ensure efficient computation. A set of test problems generated randomly based on real life data is used to evaluate the performance of the proposed algorithm. Computational results clearly indicate that GA-TS can successfully locate cost-effective solutions which are on average 20% better than that located by GA. Indeed, the proposed hybrid algorithm is an effective and efficient means for scheduling yard cranes in computer terminals.