A Comparative Study on Swarm-based Algorithms to Solve the Stochastic Optimization Problem in Container Terminal Design
This study compared swarm-based algorithms in terms of their effectiveness in improving the design of facilities in container terminals (CTs). The design was conducted within the framework of stochastic discrete optimization and involved determining the number of equipment needed in CTs by consi...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Indonesia
2020-04-01
|
| Series: | International Journal of Technology |
| Subjects: | |
| Online Access: | http://ijtech.eng.ui.ac.id/article/view/2090 |
| Summary: | This study
compared swarm-based algorithms in terms of their effectiveness in improving
the design of facilities in container terminals (CTs). The design was conducted
within the framework of stochastic discrete optimization and involved
determining the number of equipment needed in CTs by considering variations in
demand and the productivity of facilities—issues that are rarely elaborated in
CT design. Variations were identified via Monte Carlo simulation characterized by a particular
distribution. The conflicting issue due to increments in equipment investment
that possibly cause the distribution delays was also modeled, specifically in
relation to the increasing number of trucks used in terminals. Given that the
optimization problem is typified by numerous combinations of actions, the
swarm-based algorithms were deployed to develop a feasible solution. A new
variant of glowworm swarm optimization (GSO) was then proposed and compared
with particle swarm optimization (PSO) algorithms. The numerical results showed
that the performance of the proposed GSO is superior to that of PSO algorithms. |
|---|---|
| ISSN: | 2086-9614 2087-2100 |