Common due date assignment and cumulative deterioration scheduling on a single machine

Li, Shi‐Sheng; Chen, Ren-Xia

doi:10.1080/0305215x.2016.1227616

Cited by 13 publications

(3 citation statements)

References 35 publications

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“…Koulamas [17] considered the single-machine common due date assignment problem with generalized earliness and tardiness penalties and showed that the problem can be solved optimally in the polynomial time by dynamic programming. Li and Chen [9] addressed a singlemachine scheduling and common due date assignment problem in which the actual processing time of a job is a linearly increasing function of the total basic processing times of already processed jobs. Sun et al [18] studied the problem of two-machine no-wait flow shop scheduling with a learning effect and convex resource-dependent processing times.…”

Section: Literature Reviewmentioning

confidence: 99%

“…We can see that previous studies mostly discussed the common due date of the single-machine or parallel machine scheduling; thus, this study extends the common due date problem to the dynamic flow shop scheduling environment. Because the dynamic flow shop scheduling environment is an NP-hard problem [6][7][8][9], we developed the enhanced genetic algorithm. By the conventional genetic algorithm, the specific shipping dates expected by different customers are encoded to the maternal gene sequence, and thus the children are generated through the genetic evolution of crossover and mutation.…”

Section: Introductionmentioning

confidence: 99%

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The Dynamic Flow Shop Scheduling Problem with JIT Philosophy and Common Due Date

Huang

Chen

Chen³

et al. 2022

Mathematical Problems in Engineering

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Most studies on common due date problems discuss the topic in the context of solving the minimum penalty value for the single-machine or parallel machine scheduling environment. This study extends the problem of the common due date to the dynamic flow shop environment and proposes the enhanced heuristic algorithm to solve the minimum penalty value. The enhanced heuristic algorithm is characterized by designating mutant genomes of the child as the genomes located at the central location before mutation. The advantage is to integrate the successful experiences of the conventional common due date algorithm to improve the efficiency of the proposed heuristic algorithm. The performance of both algorithms is analyzed in terms of uniformly distributed job numbers, processing time, early penalty, and late penalty. The resulting outcomes indicate that the enhanced heuristic algorithm outperforms the conventional CDDA and EDD proposed by previous studies in the average penalties.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Dynamic Flow Shop Scheduling Problem with JIT Philosophy and Common Due Date

Huang

Chen

Chen³

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…In another study, mixed integer linear programming and dynamic programming methods were tested on a large data set in a single machine environment to minimize the total early delay with a common delivery date [8]. One study aimed to minimize the cost penalty function, which includes total early penalties such as delay [9]. A dynamic programming algorithm and a polynomial-time approximation scheme were proposed in another study to minimize a cost function involving the number of late jobs and the delivery date [10].…”

Section: Introductionmentioning

confidence: 99%

Determining Order Delivery Date by Revenue Approach: A Case Study With Nonwoven Textile Manufacturers in Trc1 Region

Aktürk

Gülseçen

2019

Tekstil Ve Konfeksiyon

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Non-woven textile materials are used as intermediate raw materials in various sectors such as cleaning, healthcare and automotive. These products are produced based on demand because they are requested in different compositions, colors, and weights. To ensure that the company achieves its objectives, it is necessary to use the capacity efficiently in the non-woven textile technology since it has high investment costs and high production capacity. In this study, a decision support system has been developed for non-woven textile firms so that they can obtain more order revenue. This software application was developed to sort the orders in 7 different ways based on the Moora and linear functions. The total order revenues to be obtained from each ranking and the delivery dates of sorted jobs are calculated and presented to the user to help him/her in the decision-making process. In addition, this software can also record the operator's planned maintenance data. In the present study, the decision support system was run with 27 different production scenarios. In the scenarios, the Moora method and linear function methods put forward more total order revenues than FCFS (First Come First Served) and EDD (Earliest Due Date) methods. As a product that can be used by decision-makers, the present decision support system provides a different point of view to the literature-which generally consists of theoretical studies-on delivery date and order ranking.

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Two-agent single-machine scheduling with cumulative deterioration

Chen

2018

4OR-Q J Oper Res

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Common due date assignment and cumulative deterioration scheduling on a single machine

Cited by 13 publications

References 35 publications

The Dynamic Flow Shop Scheduling Problem with JIT Philosophy and Common Due Date

The Dynamic Flow Shop Scheduling Problem with JIT Philosophy and Common Due Date

Determining Order Delivery Date by Revenue Approach: A Case Study With Nonwoven Textile Manufacturers in Trc1 Region

Two-agent single-machine scheduling with cumulative deterioration

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