Optimization Strategy for Bulk Ship Unloader Scheduling with Rail Routing Constraints

Abstract

Abstract: Based on the description of scheduling characteristics of ship unloaders, a scheduling optimization model was formulated to minimize the time for unloading operation. The components of a hybrid genetic algorithm were designed to obtain its near optimal solutions. By relaxing the complex constraints of the original problem, a lower bound for the relaxed problem was introduced to be a lower bound for the original problem. Moreover, computational experiments were conducted on instances of different sizes. The computational results show that the developed hybrid genetic algorithm can obtain reasonable solutions within an acceptable computational time.

Key words: ship unloader scheduling, mathematical programming model, lower bound, hybrid genetic algorithm

CLC Number:

TP 278

HU Da-Yong, YAO Zhen-Qiang. Optimization Strategy for Bulk Ship Unloader Scheduling with Rail Routing Constraints[J]. Journal of Shanghai Jiaotong University, 2012, 46(09): 1431-1435.

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