Earliness and tardiness scheduling problems on a batch processor

Qi, Xinyuan; Tu, Fengsheng

doi:10.1016/s0166-218x(99)00113-4

Cited by 18 publications

(9 citation statements)

References 16 publications

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“…Out of five levels of 'n', one is related to the observed week (that is, n = 1003 jobs), two are related to two extremes of the observed week (that is, extreme 1: 123 jobs per day × 7 days and the extreme 2: 180 jobs per day × 7 days), and the other two levels are randomly decided. The number of jobs, proposed in this design exceeds all the computational experiments reported in the literature of batch processor scheduling problem, including the recent one of Qi & Tu (1999).…”

Section: 1b Experimental Designmentioning

confidence: 85%

Heuristic algorithms for scheduling heat-treatment furnaces of steel casting industries

Mathirajan

Chandru

Sivakumar

2007

Sadhana

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This paper addresses a research problem of scheduling parallel, nonidentical batch processors in the presence of dynamic job arrivals, incompatible job-families and non-identical job sizes. We were led to this problem through a realworld application involving the scheduling of heat-treatment operations of steel casting. The scheduling of furnaces for heat-treatment of castings is of considerable interest as a large proportion of the total production time is the processing times of these operations. In view of the computational intractability of this type of problem, a few heuristic algorithms have been designed for maximizing the utilization of heat-treatment furnaces of steel casting manufacturing. Extensive computational experiments were carried out to compare the performance of the heuristics with the estimated optimal value (using the Weibull technique) and for relative effectiveness among the heuristics. Further, the computational experiments show that the heuristic algorithms proposed in this paper are capable of obtaining near (statistically estimated) optimal utilization of heat-treatment furnaces and are also capable of solving any large size real-life problems with a relatively low computational effort.

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Section: 1b Experimental Designmentioning

confidence: 85%

Heuristic algorithms for scheduling heat-treatment furnaces of steel casting industries

Mathirajan

Chandru

Sivakumar

2007

Sadhana

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“…Brucker, Gladky, Hoogeveen, Kovalyov, Potts, Tautenhahn and van de Velde (1998) also proved that all batch scheduling problems with the optimization function related to due date are NP-hard. Qi and Tu (1999) proposed a dynamic programming algorithm for the scheduling of a single processing machine considering distinct due dates, a common process time and identical job size to minimize sum of earliness and tardiness. Mönch, Unbehaun and Choung (2006) suggested several two-phase heuristics to the same problem applied to scheduling of a burn-in oven in the semiconductor manufacturing industry with an additional content of maximum allowable tardiness.…”

Section: Related Workmentioning

confidence: 99%

Mathematical models for a batch scheduling problem to minimize earliness and tardiness

Ogun¹,

Alabaş-Uslu²

2018

JIEM

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Abstract:Purpose: Today's manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem has been addressed to enable on-time completion of customer orders in a lean manufacturing environment. The problem is optimizing the partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components.Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid excess final product inventory. The first model is a non-linear integer programming model whereas the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings:Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times compared to the other two models. It has also been showed that the alternative model is able to solve moderate sized real-world problems. Originality/value:The problem under study differentiates from existing batch scheduling problems in the literature owing to the inclusion of new circumstances that are present in real-world applications. Those are: customer orders consisting of multi-products made of multi-parts, processing of all parts of the same product from different orders in the same batch, and delivering the orders only when all related products are completed. This research also contributes to the literature of batch scheduling problem by presenting new optimization models.

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“…Liu et al [2] considered a variety of bicriterion scheduling problems for a static single BPM in which the processing time are all equal. Qi and Tu [3] considered the earliness and tardiness (E/T) minimization problem on a single BPM in which all jobs have the same processing time and proposed a dynamic programming method to solve it. Sung et al [4] and Mӧnch et al [5] considered the same problem by Qi and Tu [3] where all jobs have unit job size.…”

Section: Introductionmentioning

confidence: 99%

“…Qi and Tu [3] considered the earliness and tardiness (E/T) minimization problem on a single BPM in which all jobs have the same processing time and proposed a dynamic programming method to solve it. Sung et al [4] and Mӧnch et al [5] considered the same problem by Qi and Tu [3] where all jobs have unit job size. Li et al [6] extended the problem of Mӧnch et al to the case of non-identical job sizes.…”

Section: Introductionmentioning

confidence: 99%

A Bi-criterion Simulated Annealing Method for a Single Batch-processing Machine Scheduling Problem with Dynamic Job Release Times

Tsai¹,

Wang²,

Chou³

2017

dtcse

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Abstract. This paper is motivated by a sterilization operation in a professional waste disposal services, and models the operation as the problem of single batch-processing machine (BPM) scheduling with the objectives of minimizing the makespan and the total weighted number of tardy orders that has not been considered in the literature. The considered problem is NP-hard such that two simulated annealing algorithms (SA1 and SA2) are developed in this work. SA1 uses multi-search directions to find Pareto-optimal solutions by eleven combinations of weights, as to SA2 applied the SMOSA of Suman to solve the considered problem. A computational experiment is conducted and the solutions for each instance obtained by SA1 and SA2 respectively are compared. Computational results reveal that SA1 is significantly better than SA2 because SA1 changes different search directions by two parameters.

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Earliness and tardiness scheduling problems on a batch processor

Cited by 18 publications

References 16 publications

Heuristic algorithms for scheduling heat-treatment furnaces of steel casting industries

Heuristic algorithms for scheduling heat-treatment furnaces of steel casting industries

Mathematical models for a batch scheduling problem to minimize earliness and tardiness

A Bi-criterion Simulated Annealing Method for a Single Batch-processing Machine Scheduling Problem with Dynamic Job Release Times

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