Scheduling yard crane in a port container terminal using genetic algorithm

It is well known that yard operation is the heart of the entire terminal as the efficiency of yard operations determines that of the overall terminal operations. To achieve smooth flow of containers in a yard, yard cranes need to be positioned at the right location at the right time to pickup containers from or load containers onto trucks. This research studies the problem of scheduling a yard crane to perform a given set of container handling jobs with different ready times to minimize the sum of job waiting times. It is shown that the problem is NP-complete. An algorithm is developed to find a lower bound for the optimal solution of the scheduling problem and genetic algorithm (GA) approach is proposed to find an effective yard crane schedule. Five popular crossover schemes are considered in this paper. The performance of GA with the five crossover schemes are evaluated on a comprehensive set of test problems which are randomly generated based on realistic yard operations data. The computational results show that the GA approach can indeed find effective solutions for the scheduling problem. Significance: The current practice of scheduling yard came in port container terminals often lead to trucks queuing up at yard blocks. The paper proposes to use GA approach to find an effective yard crane schedule to reduce the sum of truck waiting times.