Common due-date determination and sequencing using tabu search

Hao, Qi; Yang, Zihou; Wang, Dingwei; Li, Zheng

doi:10.1016/0305-0548(95)00051-8

Cited by 15 publications

(5 citation statements)

References 24 publications

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“…TS has been successfully applied to a large number of combinatorial optimization problems, including network design (Crainic et al 2000), vehicle routing (Gendreau et al 1999), and quadratic assignment (Skorin-Kapov 1990), which have shown to be competitive with other metaheuristics. TS has also been used successfully in solving scheduling problems on single machines (Hao et al 1996) and flowshops (Ben-Daya and Al-Fawzan 1998).…”

Section: Proposed Tabu Search Algorithmmentioning

confidence: 98%

A performance evaluation of permutation vs. non-permutation schedules in a flowshop

Liao

Tseng

2006

International Journal of Production Research

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It has been pointed out that a permutation schedule can be improved by a non-permutation schedule in a flowshop with completion-time based criteria, but there is a lack of comprehensive analyses. This paper presents an extensive computational investigation concerning the performance comparison between permutation and non-permutation schedules. The computational results indicate that in general, there is little improvement made by non-permutation schedules over permutation schedules with respect to completion-time based criteria. But the improvement is significant with respect to due-date based criteria, including total tardiness and total weighted tardiness. The results provide practitioners a guideline as to when to adopt a non-permutation schedule, which may exhibit better performance but require additional computational and control efforts.

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Section: Proposed Tabu Search Algorithmmentioning

confidence: 98%

A performance evaluation of permutation vs. non-permutation schedules in a flowshop

Liao

Tseng

2006

International Journal of Production Research

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“…Tabu search is a "metaheuristic" search technique proposed by Glover [17,18]. It is an effective approach to a number of NP-hard problems, such as the job-shop scheduling problem, the open-shop scheduling problem, the early/tardy machine scheduling problem, the lotsizing problem and the cell formation problem [19][20][21][22][23][24][25]. A subproblem of the team organisation problem is also NP-hard and is similar to the cell formation problem.…”

Section: Aim and Scope Of This Papermentioning

confidence: 99%

A Quantitative Approach to the Organisation of Cross-Functional Teams in Concurrent Engineering

Wang

Yan

2003

The International Journal of Advanced Manufacturing Technology

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Teamwork is one of the important features of concurrent engineering (CE). Some qualitative and conceptual models of cross-functional teams in CE and their organisation patterns have been proposed in the literature. A quantitative approach to solving the team organisation problem is needed in practice, but little work has been done on this. In this paper, a mathematical model based on integer programming is proposed to formulate the team organisation problem. In the mathematical model, the following requirements for team organisation are considered:1. The similarities between the current task and the completed tasks. 2. The technical abilities, creation abilities, management abilities, work achievements, and cooperation abilities of the developers. 3. The numbers, workloads, and utilisation rates of the developers. The team organisation problem is decomposed into a series of independent subproblems. A tabu search algorithm is proposed to solve the subproblems. And an example derived from a research institute of the Ministry of Information Industry ofChina is presented to illustrate the team organisation approach proposed in this paper. The computed result shows that the approach is feasible and the algorithm effective. By solving the subproblems one by one, we can obtain the solution to the whole team organisation problem.

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“…Recently, the use of meta-heuristics such as tabu-search (see Refs. [15][16][17], genetic algorithms 15 , simulated annealing 18 , differential evolution 19,20 , ant colony optimization [21][22][23] , artificial immune systems 24 , and Lee et al 22 addressed the restricted SMETSP with general earliness and tardiness penalties. Moreover, Biskup and Feldman 25 generated a set of benchmarks for SMETSP together with their upper bounds on the optimal objective functions.…”

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confidence: 99%

A Particle Swarm Optimization Algorithm for Scheduling Against Restrictive Common Due Dates

Nearchou¹,

Omirou²

2013

IJCIS

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Abstract:Focusing on the just-in-time (JIT) operations management, earliness as well as, tardiness of jobs' production and delivery should be discouraged. In accordance to this philosophy, scheduling problems involving earliness and tardiness penalties are very critical for the operations manager. In this paper, a new population heuristic based on the particle swarm optimization (PSO) technique is presented to solve the single machine early/tardy scheduling problem against a restrictive common due date. This type of scheduling sets costs depending on whether a job finished before (earliness), or after (tardiness) the specified due date. The objective is to minimize a summation of earliness and tardiness penalty costs, thus pushing the completion time of each job as close as possible to the due date. The problem is known to be NP-hard, and therefore large size instances cannot be addressed by traditional mathematical programming techniques. The performance of the proposed PSO heuristic is measured over benchmarks problems with up to 1000 jobs taken from the open literature, and found quite high and promising in respect to the quality of the solutions obtained. Particularly, PSO was found able to improve the 82% of the existing best known solutions of the examined benchmarks test problems.

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Common due-date determination and sequencing using tabu search

Cited by 15 publications

References 24 publications

A performance evaluation of permutation vs. non-permutation schedules in a flowshop

A performance evaluation of permutation vs. non-permutation schedules in a flowshop

A Quantitative Approach to the Organisation of Cross-Functional Teams in Concurrent Engineering

A Particle Swarm Optimization Algorithm for Scheduling Against Restrictive Common Due Dates

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