Constraint Programming Approach for Scheduling Jobs With Release Times, Non-Identical Sizes, and Incompatible Families on Parallel Batching Machines

Ham, Andy; Fowler, John W.; Cakici, Eray

doi:10.1109/tsm.2017.2740340

Cited by 28 publications

(21 citation statements)

References 28 publications

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“…For the performance evaluation of the 4.5-approximation and 2-approximation algorithms, all the instances are generated by a random algorithm, as in the papers [63][64][65][66][67][68]. In the process of the instances generation, five factors affecting the solution of the problem are determined: the number of jobs, the number of machines, the variation in job sizes, the variation in job processing time, and the variation in machine capacities [69][70][71][72][73][74][75].…”

Section: Experimental Environmentmentioning

confidence: 99%

A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem

Zhang

Song

et al. 2020

Applied Sciences

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With the rapid economic development, manufacturing enterprises are increasingly using an efficient workshop production scheduling system in an attempt to enhance their competitive position. The classical workshop production scheduling problem is far from the actual production situation, so it is difficult to apply it to production practice. In recent years, the research on machine scheduling has become a hot topic in the fields of manufacturing systems. This paper considers the batch processing machine (BPM) scheduling problem for scheduling independent jobs with arbitrary sizes. A novel fast parallel batch scheduling algorithm is put forward to minimize the makespan in this paper. Each of the machines with different capacities can only handle jobs with sizes less than the capacity of the machine. Multiple jobs can be processed as a batch simultaneously on one machine only if their total size does not exceed the machine capacity. The processing time of a batch is determined by the longest of all the jobs processed in the batch. A novel and fast 4.5-approximation algorithm is developed for the above scheduling problem. For the special case of all the jobs having the same processing times, a simple and fast 2-approximation algorithm is achieved. The experimental results show that fast algorithms further improve the competitive ratio. Compared to the optimal solutions generated by CPLEX, fast algorithms are capable of generating a feasible solution within a very short time. Fast algorithms have less computational costs.

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Section: Experimental Environmentmentioning

confidence: 99%

A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem

Zhang

Song

et al. 2020

Applied Sciences

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“…For batch scheduling problems, as the one presented in this paper, the new constraint programming solvers as the CP Optimizer available in IBM ILOG Optimization Suite (Laborie, 2009), presents some advantages compared with classical mixed-integer optimization approach, as indicated in the studies presented by Ham and Cakici (2016), Ku and Beck (2016) or in Ham et al (2017). Among other facts regarding the CP approach, the authors highlight the ability to write a more natural formulation of the problem, the flexibility and scalability of the code, and the high level description of the problem close to the engineering one where the search algorithms are automatically embedded in the CP solver.…”

Section: State-of-the-artmentioning

confidence: 99%

Optimal batch scheduling of a multiproduct dairy process using a combined optimization/constraint programming approach

Escobet¹,

Puig²,

Quevedo³

et al. 2019

Computers & Chemical Engineering

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This paper presents the optimal batch scheduling of a multi-product dairy process using an approach that combines optimization and constraint programming techniques. A suitable model describing the subprocesses and production rules is developed allowing to obtain scheduling constraints relating the production process and the machines available together with their relative efficiencies. After the scheduling problem has been formulated, the batch scheduling of a real powder milk/yogurt process is obtained in an optimal manner using the proposed approach with the objective of meeting customers' deadlines considering the efficiencies/costs of available alternative machines. Results using real consumer orders on some representative scenarios corresponding to the dairy production plant used as a case study are provided. This application shows a formulation closer to the engineering problem description thanks to the constraint-based language that facilitates the adaptation of the optimization objectives and constraints to real applications.

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“…Batch processing is a production mode that occurs widely in practice, such as in semiconductor manufacturing (Uzsoy, 1994;Ham et al, 2017), hospital sterilization (Ozturk et al, 2014), and3D printing (Kucukkoc, 2019). Two categories are generally distinguished (Mathirajan and Sivakumar, 2006), namely serial batching and parallel batching.…”

Section: Introductionmentioning

confidence: 99%

Scheduling a single parallel-batching machine with non-identical job sizes and incompatible job families

Yang¹,

Davari²,

Wei³

et al. 2021

Preprint

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We study the scheduling of jobs on a single parallel-batching machine with non-identical job sizes and incompatible job families. Jobs from the same family have the same processing time and can be loaded into a batch, as long as the batch size respects the machine capacity. The objective is to minimize the total weighted completion time. The problem combines two classic combinatorial problems, namely bin packing and single machine scheduling. We develop three new mixed-integer linear-programming formulations, namely an assignment-based formulation, a timeindexed formulation (TIF), and a set-partitioning formulation (SPF). We also propose a column generation (CG) algorithm for the SPF, which is the basis for a branch-and-price (B&P) algorithm and a CG-based heuristic. We develop a preprocessing method to reduce the formulation size. A heuristic framework based on proximity search is also developed using the TIF. The SPF and B&P can solve instances with non-unit and unit job durations to optimality with up to 80 and 150 jobs within reasonable runtime limits, respectively. The proposed heuristics perform better than the methods from the literature.

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Constraint Programming Approach for Scheduling Jobs With Release Times, Non-Identical Sizes, and Incompatible Families on Parallel Batching Machines

Cited by 28 publications

References 28 publications

A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem

A Novel Fast Parallel Batch Scheduling Algorithm for Solving the Independent Job Problem

Optimal batch scheduling of a multiproduct dairy process using a combined optimization/constraint programming approach

Scheduling a single parallel-batching machine with non-identical job sizes and incompatible job families

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