A Genetic algorithm to solve the container storage space allocation problem
This addresses a domain-specific logistics problem for port operators, but it is incremental as it applies a known method to a specific scenario.
The paper tackled the container storage space allocation problem in ports by developing a genetic algorithm to optimize container arrangement, which reduced rehandle operations and minimized ship stop time compared to a Last In First Out algorithm.
This paper presented a genetic algorithm (GA) to solve the container storage problem in the port. This problem is studied with different container types such as regular, open side, open top, tank, empty and refrigerated containers. The objective of this problem is to determine an optimal containers arrangement, which respects customers delivery deadlines, reduces the rehandle operations of containers and minimizes the stop time of the container ship. In this paper, an adaptation of the genetic algorithm to the container storage problem is detailed and some experimental results are presented and discussed. The proposed approach was compared to a Last In First Out (LIFO) algorithm applied to the same problem and has recorded good results