Hybrid Job Shop and Parallel Machine Scheduling Problems: Minimization of Total Tardiness Criterion

Dugardin, Frédéric; Chehade, Hicham; Yalaoui, Farouk; Prins, Christian

doi:10.5772/5227

Cited by 16 publications

(9 citation statements)

References 51 publications

(43 reference statements)

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“…Scheduling is defined by Pinedo (2002), Brucker (2004), and Dugardin et al (2007) as a process of allocating resources (people, equipment, or production lines) to tasks/jobs over time. The goal is to optimize (maximize or minimize) certain objectives, such as processing times or quantities, by making appropriate decisions (Dugardin et al. 2007;Fowler et al.…”

Section: Scheduling and Simulationmentioning

confidence: 99%

Automatic closed-loop scheduling in underground mining using discrete event simulation

Skawina¹,

Åstrand²,

Sundqvist³

et al. 2021

J. S. Afr. Inst. Min. Metall.

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SYNOPSIS Today's mining operations require fast reporting and rapid rescheduling based on updated information. An automatic mine scheduling system could not only quickly reschedule but also propose alternative solutions. To avoid the financial and physical risks associated with testing such a system directly in operation, it could be first evaluated via discrete event simulation models. This would offer a safe environment to evaluate different operating rules and algorithms. In this study, this is achieved by integrating automatic scheduling software with a discrete event simulation model. Keywords: discrete event simulation; production planning; scheduling system; underground mining.

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Section: Scheduling and Simulationmentioning

confidence: 99%

Automatic closed-loop scheduling in underground mining using discrete event simulation

Skawina¹,

Åstrand²,

Sundqvist³

et al. 2021

J. S. Afr. Inst. Min. Metall.

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“…For example, Bouibede-Hocine et al (2006) have used NSGA-II and SPEA algorithms for the problem. Dugardin et al (2007) have used the NSGA-II for solving a hybrid job shop and a parallel machines scheduling problem. Cochran et al (2003) have proposed a two-stage multi-population genetic algorithm (MPGA) to minimize three different criteria: makespan, the total weighted tardiness and the total weighted completion time.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristics and exact methods to solve a multiobjective parallel machines scheduling problem

Yalaoui

Chehade

2010

J Intell Manuf

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This paper deals with a multiobjective parallel machines scheduling problem. It consists in scheduling n independent jobs on m identical parallel machines. The job data such as processing times, release dates, due dates and sequence dependent setup times are considered. The goal is to optimize two different objectives: the makespan and the total tardiness. A mixed integer linear program is proposed to model the studied problem. As this problem is NPhard in the strong sense, a metaheuristic method which is the second version of the non dominated sorting genetic algorithm (NSGA-II) is proposed to solve this problem. Since the parameters setting of a genetic algorithm is difficult, a fuzzy logic controller coupled with the NSGA-II (FLC-NSGA-II) is therefore proposed. The role of the fuzzy logic is to better set the crossover and the mutation probabilities in order to update the search ability. After that, an exact method based on the two phase method is also developed. We have used four measuring criteria to compare these methods. The experimental results show the advantages and the efficiency of FLC-NSGA-II.

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“…Between machines, spots have been released to allow production buffers. CoDIT'13 978-1-4673-5549-0/13/$31.00 ©2013 IEEE stages hybrid scheduling problem is solved by Dugardin et al [4] with an ant colony optimization algorithm. Ventura and Yoon [6] propose a genetic algorithm for the case where jobs can be divided into job-lots with minimization of earliness and tardiness criteria.…”

Section: Introductionmentioning

confidence: 99%

Heuristic method for the hybrid flow shop problem in batch production

Lara¹,

Yalaoui²,

Dugardin³

et al. 2013

2013 International Conference on Control, Decision and Information Technologies (CoDIT)

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This paper deals with a hybrid flow shop scheduling problem where the objective is to minimize total tardiness. Since the described shop is hybrid, each stage could be composed of one or many identical machines. Preemption and splitting are not allowed. We suppose that machines are available to process incoming jobs without maintenance or unavailable periods. Stages are sequentially placed on the shop, so no transportation time is considered. Jobs are characterized by their release dates and due dates. Each job is composed of a given number of subjobs, which are related to a given class. Untreated subjobs are organized in batch by class in order to simplify production. A batch is composed of a single subjob class, which is associated to a processing time. Since the current problem is considered NPhard, we propose a two phases heuristic method to find suitable solutions. A mixed integer mathematical model solvable for small instances is also developed. Computational tests are performed to ensure the pertinence of proposed method.

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Hybrid Job Shop and Parallel Machine Scheduling Problems: Minimization of Total Tardiness Criterion

Cited by 16 publications

References 51 publications

Automatic closed-loop scheduling in underground mining using discrete event simulation

Automatic closed-loop scheduling in underground mining using discrete event simulation

Metaheuristics and exact methods to solve a multiobjective parallel machines scheduling problem

Heuristic method for the hybrid flow shop problem in batch production

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