Title :
Application of genetic algorithm in permutation flow shop to optimize the makespan
Author :
Pugazhenthi, R. ; Xavior, M. Anthony ; Shajahan, R. Mohamed
Author_Institution :
Sch. of Mech. & Building Sci., VIT Univ., Vellore, India
Abstract :
This paper addresses the modern manufacturing environment nature in the scheduling point of view. The scheduling is the vital criteria to allocate available resource over a period of time with one or more objective(s). The new heuristic (EPDT heuristic) is proposed for the flow shop problems to achieve the optimal makespan with the application of Genetic Algorithm (GA). This proposed heuristic approach, approximately solve the problem that consists in scheduling the jobs using Exponential Distribution factor which helps in developing a mathematical model with less computational instance. The characteristic of the heuristic was evaluated by solving Taillard benchmark problem in MATLAB environment. The EPDT heuristic yields a better result compared to classical heuristics; Palmer, CR, Gupta, and CDS heuristics.
Keywords :
exponential distribution; flow shop scheduling; genetic algorithms; resource allocation; EPDT heuristic; GA; exponential distribution factor; genetic algorithm; makespan optimization; permutation flow shop; resource allocation; Genetic algorithms; Indexes; Job shop scheduling; Mathematical model; Processor scheduling; Sequential analysis; Exponential Distribution; Flow shop; Genetic Algorithm; Heuristic; Scheduling;
Conference_Titel :
Computer Communication and Systems, 2014 International Conference on
Print_ISBN :
978-1-4799-3671-7
DOI :
10.1109/ICCCS.2014.7068186