Review on Scheduling-Job Scheduling

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2018 by IJETT Journal
Volume-60 Number-1
Year of Publication : 2018
Authors : M.Sophia.
DOI :  10.14445/22315381/IJETT-V60P205


M.Sophia. "Review on Scheduling-Job Scheduling", International Journal of Engineering Trends and Technology (IJETT), V60(1),42-44 June 2018. ISSN:2231-5381. published by seventh sense research group

Scheduling is a decision making process that plays a vital role in most manufacturing industries. The Scheduling function optimizes the limited resources allocation to the processing of jobs (Pinedo 2005). Resources include machines, robots, tools, material handling equipment and materials to be processed. A job consists of a number of operations or tasks to be done in the manufacturing system. This article discusses the development of the job shop problem and the development of methods to be used in solving JSSP. It also defines the groups JSS problems, which are divided according to the complexity of the solution. Traditional job shop scheduling is concentrated on centralized scheduling or semi distributed scheduling

[1] French.S.(1982) Sequencing and Scheduling. An introduction to the mathematics of the job-shop, New York.
[2] Blazewrcz.J, Ecker.K.H, Schmidt.G & Weglarz.J.(1984). Scheduling in computer and manufacturing systems. Berlin : Springer verlag.
[3] Pinedo.M.(2005) Planning and Scheduling in manufacturing and services. New York : Springer.
[4] Jain.A.K, & Elmaraghy.H.A, (1997). ProdutionScheudling rescheduling in flexible manufacturing. International Journal of production Research 35(1). 281-309.
[5] Ouelhadj.D, & Petroric.S.(2009b). A survey of dynamic scheduling in manufacturing system proposed by ombuki and ventresca[19].
[6] Chryssolouris.G., & Subramanian.E(2001). Dynamic Scheduling of manufacturing job shops using genetic algorithm. Journal of Intelligent & Manufacturing 12(3), 281-293.
[7] Jain A.S, & Meeran.S(1998). A state of the art review of job shop scheduling techniques.
[8] Calis.B.& Bulkan.S(2015). A research survey : Review of A1 solution strategies of job shop scheduling problem. Journal of Intelligent Manufacturing. 26(5), 961-973.
[9] Groover.M.P, Automatin Production systems and computer – Integrated Manufacturing 3rd edition. (2007), ISBN – 13 : 978-0132393218 August 3.
[10] Lageweg.B.J. Lenstra . J.K. and Rinnooykan A.H.G., Computational complexity of discrete optimization problems (1979). An Discrete Math, 4 ; 121-140.
[11] Bruchor.P., Sctile.R. Job-shop scheduling with multi-purpose machines. Computing 45(4), 369-375(1990)
[12] Graves.S.C, A review of production scheduling (1981). Operation Research, 29, 648-675.
[13] Mackay J.Elder P.A Porteous.D.JSteel.C.M. Partial delefin of chromosome IIP in beast cancer correlates with size of primary tumer and estrogen receptor level (1988).
[14] Vivers.F (1983). A decision support system for job shop scheduling. European journal of operational Research. Sep14(1), 95-103.
[15] Fezzella, F., organti.G.Ciaschetti.G, A genetic algorithm for the flexible job-shop scheduling problem(2008). Computer and operation Research Vol 35, No.10 PP 3202-3212.
[16] Fisher M.I. optional solution of scheduling problems using Lagrange multipliers. Part-I (1973). Operation Res.Vol-21, PP. 1114-1127.Journal of Scheduling 12(4), 417-431.
[17] Mastrolilli.M. Ganbordella.2M., Effective neighbourhood function for the flexible job shop problem (1996) journal of scheduling Vol-3 PP3-20.
[18] Mati.Y: Dauzore-Pores.S.Lallu CH.2011, A general approach for optimizing regular criteria in the job shop scheduling problem (2011). European journal of operation Research 212, 33-4.
[19] B.M.Ombuki and M.Ventresca. „Local search genetic algorithm for the job shop scheduling problem?. Applied intelligence, Vol 21, 2004, PP 99-109.
[20] LWang and DZ zheng, “An effective hybrid optimization strategy for job shop scheduling problems”. Comp &Oper. Res. Vol 28, 2001. PP 585-596.

Scheduling, Job Shop scheduling, scheduling problems, process layout, genetic algorithm, variable Neighbourhood, search makes fan.