Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm

Al-Hinai, Nasr; ElMekkawy, Tarek Y.

doi:10.1016/j.ijpe.2011.04.020

Cited by 203 publications

(74 citation statements)

References 92 publications

(176 reference statements)

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“…Therefore, the delivery time and the maximum completion time should be considered. At the same time, scheduling stability is also an important index needrd to be considered [9][10][11]. In order to make the research more feasible, this study is based on the following assumptions:…”

Section: The Description Of the Problem And Assumptionsmentioning

confidence: 99%

Dynamic Scheduling of Virtual Cellular Based on Rolling Window under New Tasks

Han¹,

Yu²,

Chen³

et al. 2017

Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

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Abstract. Aiming at the dynamic scheduling problem of virtual cellular generated by the random arrival of new tasks, combined with the rolling window technology, the decision-making judgment based on the order completion trigger and the machine idle state trigger is put forward. At the same time, the dynamic random scheduling period is divided into continuous interval of static scheduling. And a non-linear multi-objective 0-1 integer programming model is proposed, which is based on the maximum completion time, the weighted total delay and the initial scheduling degree of deviation as the targets. The multi-objective genetic algorithm is used to solve the model. Finally, taking the shipbuilding as an example, the feasibility and effectiveness of the rescheduling model are verified.

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Section: The Description Of the Problem And Assumptionsmentioning

confidence: 99%

Dynamic Scheduling of Virtual Cellular Based on Rolling Window under New Tasks

Han¹,

Yu²,

Chen³

et al. 2017

Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

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“…In some works, the features incorporated into the LSR-FJS definition are taken into account: lot streaming [2][3][4][5], limited machines availability [6][7][8][9][10][11], setup times [3,5,[12][13][14][15][16][17], and transport times [3,13,17]. However, these extensions are most often considered separately.…”

Section: Related Workmentioning

confidence: 99%

“…The completely reactive and predictive-reactive modes are often jointly referred to as dynamic scheduling. Algorithms supporting any of these modes are developed for the (flexible) job shop problem [6,21,22], however the off-line scheduling is the most popular.…”

Section: Related Workmentioning

confidence: 99%

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Off-Line and Dynamic Production Scheduling – A Comparative Case Study

Bożek¹,

Wysocki²

2016

Management and Production Engineering Review

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Accepted: 16 February 2016 A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also been implemented, i.e., dispatching rules for the completely reactive scheduling and a multi-agent system for the predictivereactive scheduling. In these implementations three distinct models of the problem have been used, based on: graph representation, optimal constraint satisfaction, and Petri net formalism. Each of these solutions has been verified in computational experiments. The results are compared and some findings about advantages, disadvantages, and suggestions on using the solutions are formulated.

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“…-job shop scheduling with alternative process plans -allowing for variation in technology constraint [12], -flexible job-shop scheduling problem -concerned with job scheduling in flexible production systems [13], -job shop scheduling with deteriorating jobs problem -accounting for the deterioration of working conditions over time [14], -job shop scheduling under uncertainty -the trend which is focused on scheduling in an actual production environment; often referred to as robust scheduling [15,16].…”

mentioning

confidence: 99%

Effect of Machine Failure Prediction on Selected Parameters of Manufacturing Schedule in a Job-shop Environment

Sobaszek¹,

Gola²,

Kozłowski³

2017

Topics in Economics, Business and Management (EBM)

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Production scheduling involves a number of factors, which may disrupt or completely block the smooth operation of a production processes. This paper seeks to address one of the key factors involved, machine failure, which is capable of introducing disorganisation and nervousness into production. The relevance of machine failure to production is highlighted by the extensive research in the field of robust scheduling, as a method to absorb potential disruptions. The aim of this paper is to present technological machine failure prediction method to provide the base for a robust schedule, which is subsequently verified by the mathematical model. Furthermore, the paper elaborates on the issue of scheduling in job shop environment and the idea of robust scheduling. IntroductionJob scheduling in typical manufacturing systems is the subject of numerous analyses and research works. The research is predominantly focused on scheduling problems in job-shop environments due to the fact that this is the most popular and widely applied method of organising work in production companies [1]. A problem with much of the literature regarding job scheduling is that the work is frequently based on a set of simplifications, which determine that the character of such analyses is largely theoretical [2]. Consequently, a number of problems existing in an actual scheduling of manufacturing processes are disregarded. Practice shows that each production process involves a series of factors that are counter-productive to the realisation of the process itself [3]. One problem that should not be underestimated, as it shows great potential for disrupting production, is machine failure [4]. This paper takes a new look on robust scheduling of manufacturing jobs. The scope of the analysis included technological machine failure prediction and estimation of service times. The data for simulation was obtained from historical records from the Maintenance Department of a production company. Job-shop production systems Job shop environment characteristicsIn order to model a job-shop scheduling problem the following sets must be defined [5,6]:-M, which is a set of m machines processing the jobs: --J, which is a set of n jobs to be processed:Processing job Ji on machine Mj will be referred to as operation. Therefore what must be defined is [5,6]:

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Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm

Cited by 203 publications

References 92 publications

Dynamic Scheduling of Virtual Cellular Based on Rolling Window under New Tasks

Dynamic Scheduling of Virtual Cellular Based on Rolling Window under New Tasks

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

Effect of Machine Failure Prediction on Selected Parameters of Manufacturing Schedule in a Job-shop Environment

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