Ant Foraging Behavior for Job Shop Problem

Abdul Mahad @ Abdul Hamid, Diyana and Ismail, Zuhaimy (2016) Ant Foraging Behavior for Job Shop Problem. In: MATEC Web of Conferences. EDP sciences, pp. 1005-1.

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Official URL: http://doi.org/10.1051/matecconf/20165201005

Abstract

Ant Colony Optimization (ACO) is a new algorithm approach, inspired by the foraging behavior of real ants. It has frequently been applied to many optimization problems and one such problem is in solving the job shop problem (JSP). The JSP is a finite set of jobs processed on a finite set of machine where once a job initiates processing on a given machine, it must complete processing and uninterrupted. In solving the Job Shop Scheduling problem, the process is measure by the amount of time required in completing a job known as a makespan and minimizing the makespan is the main objective of this study. In this paper, we developed an ACO algorithm to minimize the makespan. A real set of problems from a metal company in Johor bahru, producing 20 parts with jobs involving the process of clinching, tapping and power press respectively. The result from this study shows that the proposed ACO heuristics managed to produce a god result in a short time.

Item Type: Book Section
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Management (FOM)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 16 Feb 2017 03:35
Last Modified: 16 Feb 2017 03:35
URI: http://shdl.mmu.edu.my/id/eprint/6432

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