A hybrid tabu search for batching and sequencing decisions in a single machine environment

Suppiah, Yasothei; Omar, Mohamed K.

doi:10.1016/j.cie.2014.10.010

Cited by 9 publications

(4 citation statements)

References 38 publications

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“…Here, the performance measure is the sum of the tardiness and the setup costs. A tabu search approach for a single-machine s-batching problem with a maximum batch size and batch availability and the TWT measure is discussed by Suppiah and Omar (2014). Polynomial-time approaches to find Pareto-optimal schedules are established.…”

Section: Related Workmentioning

confidence: 99%

Metaheuristics for solving a flexible flow‐shop scheduling problem with s‐batching machines

Rocholl,

Mönch

2024

Int Trans Operational Res

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A scheduling problem for a two‐stage flexible flow shop with s‐batching machines motivated by processes in additive manufacturing is considered. A batch is a group of jobs that are processed together on a single machine. Each job belongs to an incompatible family. Only jobs of the same family can be batched together. A maximum batch size is given. A setup time occurs between different batches. The jobs of a batch are processed in a serial manner, that is, the processing time of a batch is the sum of the processing times of the jobs forming the batch. Batch availability is assumed. A job has a weight, a due date, and a release date. The total weighted tardiness is considered as performance measure. We establish a mixed integer linear programming formulation for this scheduling problem. For large‐sized problem instances, an iterative decomposition approach (IDA) is proposed that uses a grouping genetic algorithm or an iterated local search (ILS) scheme to solve the single‐stage subproblems. Moreover, an alternative ILS scheme based on a disjunctive graph representation of the problem at hand is designed. Results of computational experiments based on randomly generated problem instances demonstrate that the IDA hybridized with ILS outperforms the two other schemes.

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Section: Related Workmentioning

confidence: 99%

Metaheuristics for solving a flexible flow‐shop scheduling problem with s‐batching machines

Rocholl,

Mönch

2024

Int Trans Operational Res

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“…Cases with the variants of penalty times and costs, such as weighted and quadratic terms, were also studied. Total weighted tardiness was minimised in the following problem and solution approach pairs: the SDST problem that was solved using a memetic algorithm (González & Vela, 2015), the SDST problem using VNS (Kirlik & Oguz, 2012), and the problem with incompatible families and SDST using a hybrid TS (Suppiah & Omar, 2014). Total weighted tardiness and earliness were minimised by GA for a pre-emptive just-in-time (JIT) problem (Khorshidian et al, 2011), and by a hybrid between ant colony optimisation (ACO) and VNS for a JIT problem (M'Hallah & Alhajraf, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

Novel Hybrid Algorithms for a Single Machine Scheduling Problem With an Overtime Constraint

Latthawanichphan

Sukkerd

Songserm

et al. 2022

International Journal of Knowledge and Systems Science

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In this paper, a single machine scheduling problem with an overtime constraint is studied. The objective is to minimise the total penalty cost defined as the sum of tardy, early, and overtime costs. Three novel hybrid algorithms that hybridise a new heuristic with genetic algorithm, tabu search, and simulated annealing, referred to as GAH, TSH, and SAH, are proposed to solve the problem. In each iteration of the proposed hybrid algorithms, a given metaheuristic is used to determine a sequence of jobs, whereas a new heuristic is used to minimise the total penalty cost of the sequence using a backward-forward scheduling technique and a penalty cost trade-off process. Exhaustive experiments are conducted to evaluate the effectiveness of the proposed hybrid algorithms. For medium-scale and large-scale problems, TSH with its best common parameter setting referred to as TSH2, clearly outperforms the exact algorithm, whereas both algorithms can obtain the optimal solution for small-scale problems. In addition, the computational time of TSH2 is in an acceptable range for the planner.

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“…Some heuristic algorithms based on job swap moves and insert moves are presented by researchers. A hybrid tabu search algorithm for batching and sequencing decision-making in a single machine scheduling problem is proposed by Suppiah and Omar [31]. Job swapping and insertion approaches are applied to generate neighborhood solution and employed arcs in which the solution appears in the form of arcs in the tabu list to represent the sequence of job on a single machine; in addition, they also implemented a search depth strategy in the process of neighborhood generation to eliminate noneffective moves so as to reduce the computational burden while obtaining final schedule with outperformed quality.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time

Qin

2016

Scientific Programming

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A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.

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A hybrid tabu search for batching and sequencing decisions in a single machine environment

Cited by 9 publications

References 38 publications

Metaheuristics for solving a flexible flow‐shop scheduling problem with s‐batching machines

Metaheuristics for solving a flexible flow‐shop scheduling problem with s‐batching machines

Novel Hybrid Algorithms for a Single Machine Scheduling Problem With an Overtime Constraint

Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time

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