Penyelesaian Container Stowage Problem untuk Kontainer Ukuran 20 Feet menggunakan Whale Optimization Algorithm

Quinn Nathania P.J.Y, A. B. Pratiwi, H. Suprajitno
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Abstract

This paper has purpose to solve Container Stowage Problem (CSP) for 20 feet container using Whale Optimization Algorithm (WOA). CSP is a problem discussing about how to stowage a container on the ship where the purpose to minimize the unloading time. Moreover, 20 feet container is one of container types. WOA is a recently developed swarm-based metaheuristic algorithm that is based on the bubble net hunting maneuver technique of humpback whales for solving complex optimization problems. WOA had three procedures, first encircling prey, second bubble-net attacking method or exploitation phase, and third search for prey or exploration phase. WOA application program or resolving solve CSP for 20 feet container was made by using Borland C++ programming language which was implemented in three cases types of CSP data, first, the small data taking about nine containers with the number of  bays, rows and tiers, respectively, are 4, 4, 4. The second and third data was medium data and big data with 62 containers and 95 containers each data, and had the number of bays, rows and tiers, respectively, are 14, 4, 5. After executing the program can be concluded the unloading time will be better if the number of whales is larger, while the number of iterations and the number of parameter control for shape of a logaritma spiral  don’t affect the solution.
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本文旨在利用鲸鱼优化算法(WOA)解决20英尺集装箱的积载问题。CSP是一个讨论如何在船舶上装载集装箱的问题,其目的是最大限度地减少卸货时间。此外,20英尺集装箱是集装箱类型之一。WOA是近年来发展起来的一种基于群的元启发式算法,它基于座头鲸的气泡网狩猎机动技术来解决复杂的优化问题。WOA有三个阶段,第一阶段是包围猎物,第二阶段是泡泡网攻击法或利用阶段,第三阶段是寻找猎物或探索阶段。采用Borland c++编程语言编写了求解20英尺集装箱CSP的WOA应用程序,并对CSP数据的三种情况进行了实现:第一种情况,小数据约为9个集装箱,舱数、行数、层数分别为4、4、4。第二个和第三个数据是中型数据和大数据,每个数据有62个集装箱和95个集装箱,舱数为14个,行数为4个,层数为5个。执行程序后可以得出结论,鲸鱼数量越多卸载时间越好,而迭代次数和对数螺旋形状参数控制次数对解不产生影响。
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