Title: A hybrid ant colony-computer simulation approach for optimum planning and control of maritime traffic

Authors: Mohammad Ali Azadeh; Babak Maleki Shoja; Pooyan Kazemian; Zahra Tavassoli Hojati

Addresses: Department of Industrial Engineering, Center of Excellence for Intelligent Based Experimental Mechanics, University of Tehran, Kargar Shomali St., Tehran, Iran; Department of Engineering Optimisation Research, College of Engineering, University of Tehran, Kargar Shomali St., Tehran, Iran ' Department of Industrial Engineering, Center of Excellence for Intelligent Based Experimental Mechanics, University of Tehran, Kargar Shomali St., Tehran, Iran ' Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, USA1205 Beal Ave., Ann Arbor, USA ' Department of Industrial Engineering, Center of Excellence for Intelligent Based Experimental Mechanics, University of Tehran, Kargar Shomali St., Tehran, Iran

Abstract: Ant colony optimisation (ACO) is a meta-heuristic approach to tackle hard combinatorial optimisation problems which has been used to solve several optimisation problems in various fields of engineering. Its basic component is a probabilistic solution construction mechanism. Discrete event simulation (DES) is a method which is used to model real world systems capable of being decomposed into a set of logically separate processes autonomously progressing through time. Each event occurs at an instant of time and indicates a change of state in the system. In this paper, we present the application of ant colony optimisation (ACO) model in discrete event simulation of marine traffic. We use this methodology to compare different distribution functions and to find the best distribution with its associated parameters. We experimentally show that exponential distribution has the best results for creating the simulation events of maritime traffic in Arvand river, Iran. Also, the integrated ACO-DES finds the best exponential distribution parameters for arrival (planning and control) of different kinds of ships in one of the most hazardous, crowded, and potentially dangerous rivers in the world. This is the first study that integrates ACO with DES for identification and optimisation of maritime traffic.

Keywords: ant colony optimisation; ACO; discrete event simulation; DES; distribution functions; maritime traffic control; Iran; ships; ship arrival planning; ship arrival control; river traffic.

DOI: 10.1504/IJISE.2013.055512

International Journal of Industrial and Systems Engineering, 2013 Vol.15 No.1, pp.69 - 89

Published online: 27 Dec 2013 *

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