Paper Information

Journal:   SCIENTIA IRANICA   2014 , Volume 21 , Number 3 (TRANSACTIONS E: INDUSTRIAL ENGINEERING); Page(s) 1007 To 1020.
 
Paper: 

AN ENHANCED INVASIVE WEED OPTIMIZATION FOR MAKESPAN MINIMIZATION IN A EXIBLE OWSHOP SCHEDULING PROBLEM

 
 
Author(s):  JOLAI F.*, TAVAKKOLI MOGHADDAMA R., RABIEE M., GHEISARIHA E.
 
* SCHOOL OF INDUSTRIAL ENGINEERING, COLLEGE OF ENGINEERING, UNIVERSITY OF TEHRAN, TEHRAN, IRAN
 
Abstract: 

In previous investigations in the eld of exible ow shop scheduling problems, the rework probability for operations was ignored. As these kinds of problems are NPhard, we present an Enhanced Invasive Weed Optimization (EIWO) algorithm in order to solve the addressed problem with probable rework times, transportation times with a conveyor between two subsequent stages, dierent ready times and anticipatory sequence dependent setup times. The optimization criterion is to minimize makespan. Although Invasive Weed Optimization (IWO) is an ecient meta-heuristic algorithm and has been used by many researchers recently, to increase the capability of IWO, we added a mutation operation to enhance the exploration in order to prevent sticking in local optimum. In addition, an anity function is embedded to obstruct premature convergence. With these changes, we balance the exploration and exploitation of IWO. Since the performance of our proposed algorithm depends on parameters values, we apply the popular design of an experimental methodology, called the Response Surface Method (RSM). To evaluate the proposed algorithm, rst, some random test problems are generated and compared with three benchmark algorithms. The related results are analyzed by statistical tools. The experimental results and statistical analyses demonstrate that the proposed EIWO is eective for the problem.

 
Keyword(s): IWO, FLEXIBLE OW SHOP, RESPONSE SURFACE METHODOLOGY, REWORK, TRANSPORTATION TIME, ANTICIPATORY SEQUENCE DEPENDENT SETUP TIME
 
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