OCTOBER 19-20, 2012 - YMCA University of Science & Technology

Proceedings of the National Conference on
Trends and Advances in Mechanical Engineering,
YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012
6. Conclusions:
In this work scheduling problem in a real time job shop environment is solved, for the single objective
problem to minimize(optimization) the make span (C max ) . This objective is chosen because minimizing the make
span results into minimizing the manufacturing lead time. An asexual reproduction genetic algorithm with mutation
strategies is used to solve the scheduling problem.
In order to evaluate the effectiveness of the source code developed in MATLAB, it is first tested on the benchmark
problem [15] and later on, on several other problems [16]. The experimentations with these problems confirmed
that the source code developed in MATLAB is able to find good solutions of the addressed problem . Results
lie between the limits of upper bound & lower bound values [15] which are stated in various literatures, related to job
shop scheduling problems.
Overall the results indicate that the source code developed for finding the performance of this job shop scheduling
problem is able to generate the results which are comparable or better than the literature associated with this
problem. Currently, the source code generates the schedule which lies within the lower bound and upper bound of
the bench mark instances [15] taken from the literature.
References
[1] Falkenauer, E., and Bouffouix, S., (1991),” A Genetic Algorithm for the Job- Shop”, Proceedings of
the IEEE International Conference on Robotics and Automation, Sacremento, California, USA, pp. 824-
829.
[2] Low. C,Hsu, C.-M., Huang, K.I., 2004. “Benefits of lot splitting in job-shop scheduling”, International Journal
of Advanced Manufacturing Technology 24, 773–780
[3] Artigues, C., Roubellat, F., 2002 “An efficient algorithm for operation insertion in a multi-resource job-shop
scheduling with sequence-dependent setup times”,Production Planning and Control 13, 175–186.
[4] Yaqin,Zhou et al. 2005. “Job shop scheduling problems with setups using biological immune algorithm”.
[5] Balas, E., Simonetti, N., Vazacopoulos, A., 2005. “Job shop scheduling with setup times,deadlines and
precedence constraints”, In: Proceedings of the 2nd Multidisciplinary International Conference on Scheduling:
Theory and Applications, New York, USA, July 18–21, 2005, pp. 520–532
[6] Cheung, W., Zhou, H., 2001. “Using genetic algorithms and heuristics for job shop scheduling with sequencedependent
setup times”, Annals of Operations Research 107, 65–81.
.[7 French, S., (1982), “Sequencing and Scheduling - An Introduction to the Mathematics of the Job-Shop”,
John-Wiley and Sons, New York. 168, 1990.
[8] Camino, Ramiro., 2008. “Proposed a hybrid algorithm called mimetic algorithm for job shop scheduling
for job shop scheduling with setup times with the objective of make span minimization”.
[9] Choi, I.C., Choi, D.S., 2002. “A local search algorithm for jobshop scheduling problems with alternative
operations and sequence-dependent setups”, Computers and Industrial Engineering 42, 43–58.
[10] Ballicu, M., Giua, A., Seatzu, C., 2002. “Job-shop scheduling models with set-up times”, Proceedings of the
IEEE International Conference on Systems, Man and Cybernetics 5, 95–100.
[11 Pinedo, M., (2001), “Scheduling: Theory, Algorithms, and Systems”, Prentice Hall, New York. Third
edition.pp.18.
[12] .Marco Ballicu , Alessandro Giua 2002. “Studied the classical representation job shop scheduling problems in
terms of disjunctive graphs”. Their objective was minimization of makespan.
[13] Manikas , Chang 2009. “Studied a multi-objective job shop scheduling problem with separable sequencedependent
setups”.
[14] Ali Allahverdi ,H.M.Soroush “A survey of scheduling problems about the significance of reducing setup times
or costs”, European Journal of Operational Research 187 (2008) 978–984.
[15] E.Taillard,1992. “Benchmarks for basic scheduling problems” Ecole Polytechnique Fdddrale de Lausanne,
Departement de Mathmatiques, CH-1015 Lausanne,Switzerland.
[16] Tsuyoshi Satake, Katsumi Morikawa, Katsuhiko Takahashi, Nobuto Nakamura 1999, “Simulated annealing
approach for minimizing the makespanof the general job-shop”.
[17] Focacci et al “Solving scheduling problems with setup times and alternative resources”, In: Proceedings of the
Fifth International Conference on Artificial Intelligence Planning and Scheduling, Breckenbridge, Colorado,
USA, pp. 92–101.
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