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Optimization of Total Holding Cost in Job shop scheduling by using
Hybrid Algorithm
S.Gobinath
1,a
, C.Arumugam
2,b
, G.Ramya
3,c
, M.Chandrasekaran
4,d
1,a Asso.Prof, Dept of Mechanical Engg, Kongunadu College of Engineering and Technology,
Trichy Dist
2,a Coimbatore Institute of Technology, Coimbatore
3,c Sathyabama University, Chennai.
4,d Department of Mechanical Engg, Vels University, Chennai.
* nithnathdeep@yahoo.com (corresponding author)
Keywords: Job shop scheduling, Hybrid Algorithm, Artificial Immune System and Sheep Flock
Heredity Model Algorithm.
Abstract
The classical job-shop scheduling problem is one of the most difficult combinatorial
optimization problems. Scheduling is defined as the art of assigning resources to tasks in order to
insure the termination of these tasks in a reasonable amount of time. Job shop scheduling problems
vary widely according to specific production tasks but most are NP-hard problems. Mathematical
and heuristic methods are the two major methods for resolving JSP. Job shop Scheduling problems
are usually solved using heuristics to get optimal or near optimal solutions. In this paper, a Hybrid
algorithm combined artificial immune system and sheep flock heredity model algorithm is used for
minimizing the total holding cost for different size benchmark problems. The results show that the
proposed hybrid algorithm is an effective algorithm that gives better results than other hybrid
algorithms compared in literature. The proposed hybrid algorithm is a good technique for
scheduling problems.
Introduction
The job shop problem is the most complicated and typical problem of all kinds of
production scheduling problems. The main objective is focusing the process of arranging processing
orders and times of operations on the same machine. The n-job, m-machine Job shop scheduling
(JSP) problem is one of the general scheduling problems in a system. Also, the problem of
scheduling is addressed after the job orders are released into the shop floor, along with their process
plans and machine routings. Scheduling problems are normally Non-Polynomial (NP) hard, so it is
very difficult to find an optimal solutions [1]. Optimization methods attempt to find the optimal
solution through mathematical programming techniques or methods According to the market
demand, the scheduling objectives are classified into two types. One is Time based minimization
and second is Cost based minimization. The objectives considered under the time minimization are
minimize machine idle time, Minimize the mean flow time, Minimize the mean tardiness. The
objectives considered under the cost minimization are minimize the costs due to not meeting the
due dates, Minimize the lateness cost, Minimize the total holding cost with no tardy jobs and with
tardy jobs. The most important target in scheduling is meeting the due dates for each job that has
been associated with customer. Due dates are treated as deadlines and every job must be completed
before or just on its due date and no tardy jobs are allowed. The total holding cost means the sum of
product inventory coscost and in-process inventory t. The job-shop scheduling problem of
minimizing the total holding cost of completed and in-process products subject to no tardy jobs is to
be considered to deliver all the jobs with proper due date.
Researchers turned to search its near optimal solutions with all kind of heuristic algorithms
[2]. A hybrid particle swarm optimization approach for the job shop scheduling problems. It
Applied Mechanics and Materials Submitted: 2014-05-10
ISSN: 1662-7482, Vol. 591, pp 176-179 Revised: 2014-05-20
doi:10.4028/www.scientific.net/AMM.591.176 Accepted: 2014-05-20
© 2014 Trans Tech Publications Ltd, All Rights Reserved Online: 2014-07-18
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