Simulated annealing-based ant colony algorithm for tugboat scheduling optimization
type: Item
instance of: scholarly article
title: Simulated annealing-based ant colony algorithm for tugboat scheduling optimization
zbMATH Open document ID: 1264.90189
DOI: 10.1155/2012/246978
author: Qi Xu
author: Jun Mao
author: Zhihong Jin
published in: Mathematical Problems in Engineering
publication date: 2013-06-11T00:00:00Z
review text: Summary: As the ``first service station'' for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP) after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting-berth/unberthing). The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing-based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting-berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting-berth operation, one can see that the objective is most sensitive to the proportion of the shifting-berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 90B90
Mathematics Subject Classification ID: 90B35
zbMATH DE Number: 6173124
Wikidata QID: Q58911330
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/246978
OpenAlex ID: W2171373390
cites work: Multiprocessor task scheduling in multistage hybrid flow-shops: an ant colony system approach
description: scientific article; zbMATH DE number 6173124