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Hybrid Genetic Algorithm for Multicriteria Scheduling with Sequence Dependent Set up Time
Ashwani Dhingra, Pankaj Chandna
Pages - 510 - 520     |    Revised - 30-10-2009     |    Published - 30-11-2009
Volume - 3   Issue - 5    |    Publication Date - November 2009  Table of Contents
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KEYWORDS
UWB, Indoor wireless systems, Keil IDE
ABSTRACT
In this work, multicriteria decision making objective for flow shop scheduling with sequence dependent set up time and due dates have been developed. Multicriteria decision making objective includes total tardiness , total earliness and makespan simultaneously which is very effective decision making for scheduling jobs in modern manufacturing environment. As problem of flow shop scheduling is NP hard and to solve this in a reasonable time, four Special heuristics (SH) based Hybrid Genetic Algorithm (HGA) have also been developed for proposed multicriteria objective function. A computational analysis upto 200 jobs and 20 machines problems has been conducted to evaluate the performance of four HGA’s. The analysis showed the superiority of SH1 based HGA for small size and SH3 based HGA for large size problem for multicriteria flow shop scheduling with sequence dependent set up time and due dates. Keywords: Flow shop scheduling, Genetic algorithm, Sequence dependent set up time, Total tardiness, Total earliness, makespan
CITED BY (19)  
1 adhi, a. (2015). Model sistem perencanaan produksi terintegrasi di industri percetakan. jurnal ilmiah dinamika teknik, 8(1).
2 Marichelvam, M. K., & Prabaharan, T. (2015). Solving realistic industrial scheduling problems using a multi–objective improved hybrid particle swarm optimisation algorithm. International Journal of Operational Research, 23(1), 94-129.
3 Akande, S., Oluleye, A. E., & Oyetunji, E. O. (2015, March). On the reducibility of multicriteria scheduling problems to bicriteria scheduling problems. In Industrial Engineering and Operations Management (IEOM), 2015 International Conference on (pp. 1-8). IEEE.
4 Akande, S. A., & Ajisegiri, G. O. Performance Measure of Multipurpose Machine From Single Machine Units.
5 Gupta, B. Comparative Study of Genetic Operators and Parameters for Multiprocessor Task Scheduling.
6 Akande, S., Oluleye, A. E., & Oyetunji, E. O. (2014, January). Reducibility of Some Multi Criteria Scheduling Problems to Bicriteria Scheduling Problems. In Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia.
7 Dalfard, V. M., Kaveh, M., & Nosratian, N. E. (2013). Two meta-heuristic algorithms for two-echelon location-routing problem with vehicle fleet capacity and maximum route length constraints. Neural Computing and Applications, 23(7-8), 2341-2349.
8 Werner, F. (2013). A survey of genetic algorithms for shop scheduling problems. P. Siarry: Heuristics: Theory and Applications, Nova Science Publishers, 161-222.
9 Filho, M. G., de Fátima Morais, M., Boiko, T. J. P., Miyata, H. H., & Varolo, F. W. R. (2013). Scheduling in flow shop with sequence-dependent setup times: literature review and analysis. International Journal of Business Innovation and Research, 7(4), 466-486.
10 Gupta, B., & Dhingra, S. (2013). Analysis of Genetic Algorithm for Multiprocessor Task Scheduling Problem. International Journal, 3(7).
11 V. M. Dalfard, M. Ahmadpour, O. Jalilian and H. Jalilian, “Optimization of net present value of total net profits of client and contractor in payments of client to contactor by the use of hybrid genetic algorithm”, African Journal of Business Management, 6(5), pp. 2034-2042, Feb. 2012.
12 Narendhar, S., & Amudha, T. (2012). A Hybrid Bacterial Foraging Algorithm for Solving Job Shop Scheduling Problems. arXiv preprint arXiv:1211.4971.
13 Dalfard, V. M., & Mohammadi, G. (2012). Two meta-heuristic algorithms for solving multi-objective flexible job-shop scheduling with parallel machine and maintenance constraints. Computers & Mathematics with Applications, 64(6), 2111-2117.
14 Zhang, D. (2012). Radio Resource Management based on Genetic Algorithms for OFDMA Networks (Doctoral dissertation, Queen Mary University of London).
15 Majazi Dalfard, V., Ardakani, A., & Nazalsadat Banihashemi, T. (2011). Hybrid genetic algorithm for assembly flow-shop scheduling problem with sequence-dependent setup and transportation times. Tehnicki vjesnik, 18(4), 497-504.
16 S. Najafi, V. M. Dalfard and G. Mohammadi, “Hybrid genetic algorithm for network locating problem by considering multi-purpose trip in stochastic state”, Indian Journal of Science and Technology , 4(9), pp. 1109-1112, Sep. 2011.
17 K. M. Senthilkuma, V. Selladurai, K. Raja and V. Thirunavukkarasu, “A Hybrid Algorithm Based on PSO and ACO Approach for Solving Combinatorial Fuzzy Unrelated Parallel Machine Scheduling Problem”, European Journal of Scientific Research, 64(2), pp. 293-313, 2011.
18 P. Arikaran , Dr. V. Jayabalan and R. Senthilkumar, “Analysis of Unequal Areas Facility Layout Problems”, International Journal of Engineering (IJE), 4(1), pp. 44 – 51, Mar. 2010.
19 A. Dhingra and P. Chandna, “A bi-criteria M-machine SDST flow shop scheduling using modified heuristic genetic algorithm”, International Journal of Engineering, Science and Technology, 2(5), pp. 216-225, 2010.
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Allahverdi A., Ng C.T., Cheng T.C.E. and Kovalyov M.Y. “A survey of scheduling problems with setup times or costs”. European Journal of Operation Research, 187(3):985–1032,2008
Blazewicz J, Pesch E, Sterna M and Werner F. “ A comparison of solution procedures for two-machine flow shop scheduling with late work criterion”. Computers and Industrial Engineering, 49:611–624,2005
Danneberg D., Tautenhahn T., Werner F. “A comparison of heuristic algorithms for flow shop scheduling problems with setup times and limited batch size”. Mathematical and Computer Modelling, 29 (9):101–126,1999
Eren, T. “A bicriteria m-machine flow shop scheduling with sequence-dependent setup times”. Applied Mathematical Modelling,2009 (In press), doi: 10.1016/j.apm.2009.04.005
Erenay F.S., et al. “New solution methods for single machine bicriteria Scheduling problem: Minimization of average flow time and number of tardy jobs”. European Journal of Operational Research,2009 (In press), doi:10.1016/j.ejor.2009.02.014
Fred Choobineh F., Mohebbi E. and Khoo, H. “A multi-objective tabu search for a single-machine scheduling problem with sequence dependent setup times”. European Journal of Operational Research, 175, 318–337,2006
Gowrisankar K, Chandrasekharan Rajendran and Srinivasan G. “Flow shop scheduling algorithm for minimizing the completion time variance and the sum of squares of completion time deviations from a common due date”. European Journal of Operation Research, 132:643–665,2001
Gupta J.N.D., Venkata G., Neppalli R. and Werner F. “Minimizing total flow time in a two-machine flowshop problem with minimum makespan”. International Journal of Production Economics, 69:323–338,2001
Lockett A. G. and Muhlemann A. P. “Technical notes: a scheduling problem involving sequence dependent changeover times”.Operation Research, 20: 895-902,1972
Loukil T., Teghem J. and Tuyttens D. “Solving multi-objective production scheduling problems using metaheuristics”. European Journal of Operation Research , 161(1) :42–61,2005
Naderi B., Zandieh M. and Roshanaei V. “Scheduling hybrid flowshops with sequence dependent setup times to minimize makespan and maximum tardiness”. International Journal of Advanced Manufacturing Technology, 41:1186–1198,2009
Nawaz M., Enscore E. and Ham I. “Heuristic Algorithm for the M-Machine N-Job Flow Shop Sequencing Problem”. Omega, 11: 91–95,1983
Noorul Haq and Radha Ramanan T. “A bicriterian flow shops scheduling using artificial neural network”. International Journal of Advanced Manufacturing Technology, 30: 1132–1138, 2006
Ponnambalam S. G., Jagannathan H., Kataria M. and Gadicherla A. “A TSP-GA multi-objective algorithm for flow shop scheduling”. International Journal of Advanced Manufacturing Technology, 23: 909–915,2004
Rahimi Vahed R and Mirghorbani S. M. “A multi-objective particle swarm for a flow shop scheduling problem”. Combinatorial Optimization, 13 (1):79–102,2007
Rajendran C. “Theory and methodology heuristics for scheduling in flow shop with multiple objectives” .European Journal of Operation Research , 82 (3):540 ?555,1995
Ravindran D., Noorul Haq A., Selvakuar S.J. and Sivaraman R. “ Flow shop scheduling with multiple objective of minimizing makespan and total flow time”. International Journal of Advanced Manufacturing Technology, 25:1007–1012,2005
Sayin S. and Karabati S. “A bicriteria approach to the two-machine flow shop scheduling problem”. European Journal of Operation Research, 113:435–449,1999
Taillard E. “Benchmarks of basic scheduling problems”. European Journal of Operation Research, 64:278–285, 1993
Toktas B., Azizoglu M. and Koksalan S.K. “Two-machine flow shop scheduling with two criteria: Maximum earliness and makespan”. European Journal of Operation Research, 157(2): 286–295,2004
Mr. Ashwani Dhingra
- India
ashwani_dhingra1979@rediff.com
Dr. Pankaj Chandna
National Institute of Technology - India


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