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
METAHEURISTIC DESIGNED FOR CALCULATING MAKESPAN OF
COMPREHENSIVE SCHEDULING PROBLEMS
Sunil Kumar 1 , Rajender Kumar Tayal 2
1 Prannath Parnami Institute of Management &Technology, Hisar (Haryana)
2 Government Polytechnic Sirsa (Haryana)
e-mail: sunilchander1984@gmailmail.com
Abstract:
Scheduling is necessary to deal with internal and external disruption faced in real life manufacturing environments.
Scheduling is a process of allocation of resources to tasks over a given time period. The objective of scheduling is to
ensure maximum utilization of the plant at minimum cost. Main objective of the problem is to determine best job
sequence that optimizes the makespan (C max ) i.e. total completion time of the job for a job shop problem . In addition
to makespan various factors like completion time of the jobs on each machine, machine loading time, machine idle
time among all these machines are also determined. An asexual reproduction genetic algorithm with mutation
strategies is developed to solve the single-objective job shop scheduling with setup time. A source code is developed
in MATLAB to solve the aforesaid problem and it is tested on various bench mark problems and other problems
taken from literature. Results are compared with those available in the literature associated with this problem. The
findings indicate that the source code developed in MATLAB using genetic algorithm can find good solutions within
a very short computational time.
Key Words: Job Shop Scheduling, Genetic Algorithm, Makespan.
1. INTRODUCTION
Scheduling is the process of deciding how to commit resources between varieties of possible tasks. It is a decisionmaking
process in which allocation of resources to tasks over given time period [7]. Single machine shop, Parallel
machine shop, Flow shop, Flexible flow shop, Job shop, Flexible job shop and Open shop are various types of
scheduling shop. In job shop the order in which jobs visits the machines is different and objective is to determine the
order or sequence for processing a set of jobs through several machines in an optimal manner. Job shop scheduling
problem received considerable attention in the literature and as a consequence a variety of scheduling algorithms or
procedures for certain types of job shops were evolved.
2. Literature review
Various research work’s on scheduling were conducted by Indian and international scientists. Some of the basic
literature papers have been collected for the study, these are mainly related to job shop scheduling problem. Sun et
al. [13] addressed the job shop scheduling problem with release dates due dates and sequence dependent setup times
with the scheduling objective to minimize the weighted sum of squared tardiness (maximum (lateness,0)). The
problem is NP – hard whose optimal solution is difficult to obtain. Focacci et al. [17] addressed the job shop
scheduling problem with sequence dependent setup times and alternative resources where optimization criteria are
both make span and sum of setup times. Artigues and Roubellat [18] presented a Petri net approach for on-line and
off-line scheduling of a job shop with job release dates, sequence dependent family setup times and the maximum
lateness objective. Cheung and Zhou [6] addressed the job shop problem with separable sequence dependent setup
times. The objective of their problem was to minimize makespan, (i.e. the completion times of all jobs) they first
described the problem with a mixed integer programming model. Marco Ballicu et al. [12] considered the classical
representation job shop scheduling problems in terms of disjunctive graphs. Their objective was minimization of
makespan. Chan Choi and Dae-Sik Choi [9] considered job shop scheduling problem with alternative operations and
sequence-dependent setups. Artigues et al. [19] proposed a new exact solution algorithm for the job shop problem
with sequence-dependent setup times Balas et al. [5] deal with a variant of the job shop scheduling problem. Yaqin
Zhou et al. [4] solved the job shop scheduling problems with setups using biological immune algorithm. Manikas
and Chang [13] studied a multi-objective job shop scheduling problem with separable sequence-dependent setups.
Aldakhilallab and Ramesh [20] proposed cyclic scheduling for a job shop manufacturing environment. Two efficient
cyclic scheduling heuristic for job shop environments were developed. Each heuristic generate an efficient and
feasible cycle production schedule for a job shop in which a single product was produced repetitively on a set of
machines was to determine an efficient and feasible cyclic schedule which simultaneously minimizes flow time and
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