The Lessons of Flowshop Scheduling Research

Dudek, R. A.; Panwalkar, S. S.; Smith, Milton L.

doi:10.1287/opre.40.1.7

Cited by 192 publications

(70 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Given this, one could think that then the concept of flowshop scheduling with random instances is a moot issue. However, let us recall that a flowshop is a simplification of reality and as indicated by Dudek et al (1992), real problems have many more additional constraints. In any case, using hard random instances in benchmarks is an accepted norm in the field of operations research.…”

Section: Flowshop Scheduling Problem and The Hardness Of The Instancesmentioning

confidence: 99%

New hard benchmark for flowshop scheduling problems minimising makespan

Vallada

Ruíz

Framiñán

2015

European Journal of Operational Research

149

View full text Add to dashboard Cite

In this work a new benchmark of hard instances for the permutation flowshop scheduling problem with the objective of minimising the makespan is proposed. The new benchmark consists of 240 large instances and 240 small instances with up to 800 jobs and 60 machines. One of the objectives of the work is to generate a benchmark which satisfies the desired characteristics of any benchmark: comprehensive, amenable for statistical analysis and discriminant when several algorithms are compared. An exhaustive experimental procedure is carried out in order to select the hard instances, generating thousands of instances and selecting the hardest ones from the point of view of a gap computed as the difference between very good upper and lower bounds for each instance. Extensive generation and computational experiments, which have taken almost six years of combined CPU time, demonstrate that the proposed benchmark is harder and with more discriminant power than the most common benchmark from the literature. Moreover, a website is developed for researchers in order to share sets of instances, best known solutions and lower bounds, etc. for any combinatorial optimisation problem.

show abstract

Section: Flowshop Scheduling Problem and The Hardness Of The Instancesmentioning

confidence: 99%

New hard benchmark for flowshop scheduling problems minimising makespan

Vallada

Ruíz

Framiñán

2015

European Journal of Operational Research

149

View full text Add to dashboard Cite

show abstract

“…Preemptions are not allowed, that is, when a job starts to be processed on a machine, it cannot be interrupted. Among its several applications, one of the most relevant applications of flowshop can be found in the chemical industry [3,13]. Since specific equipment for chemical processes is expensive, there is a strong motivation to optimize this production environment.…”

Section: Introductionmentioning

confidence: 99%

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Ronconi

Birgin

2011

Just-in-Time Systems

View full text Add to dashboard Cite

Scheduling problems involving both earliness and tardiness costs have received significant attention in recent years. This type of problem became important with the advent of the justin-time (JIT) concept, where early or tardy deliveries are highly discouraged. In this work we examine the flowshop scheduling problem with no storage constraints and with blocking inprocess. In this latter environment, there are no buffers between successive machines; therefore intermediate queues of jobs waiting in the system for their next operations are not allowed. Performance is measured by the minimization of the sum of earliness and tardiness of the jobs. Mixed-integer models that represent these scheduling flowshop problems are presented. The models are evaluated and compared in several problems using commercial known software.

show abstract

“…For a review of the general flowshop problem, see [2], and more recently [3]. The application of the flowshop scheduling research can be found in the areas such as chemical process industry and manufacturing systems, especially flexible transfer or assembly lines in which a wide range of parts are manufactured [4].…”

Section: Introductionmentioning

confidence: 99%

Parallelization of a Branch and Bound Algorithm on Multicore Systems

Chung

Flynn

Sang

2012

JSEA

View full text Add to dashboard Cite

The general m-machine permutation flowshop problem with the total flow-time objective is known to be NP-hard for m ≥ 2. The only practical method for finding optimal solutions has been branch-and-bound algorithms. In this paper, we present an improved sequential algorithm which is based on a strict alternation of Generation and Exploration execution modes as well as Depth-First/Best-First hybrid strategies. The experimental results show that the proposed scheme exhibits improved performance compared with the algorithm in [1]. More importantly, our method can be easily extended and implemented with lightweight threads to speed up the execution times. Good speedups can be obtained on shared-memory multicore systems.

show abstract

The Lessons of Flowshop Scheduling Research

Cited by 192 publications

References 42 publications

New hard benchmark for flowshop scheduling problems minimising makespan

New hard benchmark for flowshop scheduling problems minimising makespan

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Parallelization of a Branch and Bound Algorithm on Multicore Systems

Contact Info

Product

Resources

About