Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems

Pagnozzi, Federico; Stützle, Thomas

doi:10.1016/j.ejor.2019.01.018

Cited by 39 publications

(28 citation statements)

References 48 publications

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“…This outline also defines the ways the algorithmic components can be combined. The implementation itself is done in the EMILI framework [71], which aims at a flexible combination of algorithm components that makes it particularly amenable to automatic configuration.…”

Section: Methodsmentioning

confidence: 99%

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Revisiting simulated annealing: A component-based analysis

Franzin

Stützle

2019

Computers & Operations Research

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105

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Simulated Annealing (SA) is one of the oldest metaheuristics and has been adapted to solve many combinatorial optimization problems. Over the years, many authors have proposed both general and problem-specific improvements and variants of SA. We propose to accumulate this knowledge into automatically configurable, algorithmic frameworks so that for new applications that wealth of alternative algorithmic components is directly available for the algorithm designer without further manual intervention. Here, we describe SA as an ensemble of algorithmic components, and describe SA variants from the literature within these components. We show the advantages of our proposal by (i) implementing existing algorithmic components of variants of SA, (ii) studying SA algorithms proposed in the literature, (iii) improving SA performance by automatically designing new state-ofthe-art SA implementations and (iv) studying the role and impact of the algorithmic components based on experimental data. Our experiments consider three common combinatorial optimization problems, the quadratic assignment problem and two variants of the permutation flow shop problem.

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Section: Methodsmentioning

confidence: 99%

“…As mentioned above, we implemented the SA components within the EMILI framework [71]. As the automatic algorithm configuration tool we use irace [76,19], which is an R implementation of the Iterated Racing algorithm [77,78].…”

Section: Methodsmentioning

confidence: 99%

Revisiting simulated annealing: A component-based analysis

Franzin

Stützle

2019

Computers & Operations Research

Self Cite

105

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“…They have also experimentally demonstrated the potential of this new approach on three well-known combinatorial optimization problems, such as quadratic assignment problem and two variants of the permutation flow shop problem. Pagnozzi and Stützle [12] presented an automatic design of hybrid SLS algorithms for permutation flowshop problems (PFSP). Here, they automatically generated a new state-of-the-art algorithm for some of the most widely studied variants of the PFSP.…”

Section: Automatic Configuration Of Sls Algorithmsmentioning

confidence: 99%

“…A lot of work related to algorithm engineering has been done by research community with regard on automatic algorithm configuration and parameter tuning techniques. Examples of these include ParamILS algorithm introduced by Hutter et al [8], automated algorithms configuration and parameter tuning presented by Hoos in [9], automatic design of hybrid SLS algorithms by Marmion et al, [10], grammar-based generation of SLS heuristics by Mascia et al [11], permutation flowshop problems by Pagnozzi and Stützle [12], algorithm comparison by automatically configurable SLS frameworks by Mascia et al, [13], revisiting simulated annealing by Franzin and Stützle [14]. On the other side, Franzin et al, [15] studied the effect of transformations for numerical parameters, Franzin and Stützle [16] performed comparison of acceptance criteria in randomized local searches, Mu et al, [17] conducted a research on the impact of automated algorithm configuration etc.…”

Section: Introductionmentioning

confidence: 99%

Stochastic local search: a state-of-the-art review

Kastrati¹,

Biba²

2021

IJECE

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The main objective of this paper is to provide a state-of-the-art review, analyze and discuss stochastic local search techniques used for solving hard combinatorial problems. It begins with a short introduction, motivation and some basic notation on combinatorial problems, search paradigms and other relevant features of searching techniques as needed for background. In the following a brief overview of the stochastic local search methods along with an analysis of the state-of-the-art stochastic local search algorithms is given. Finally, the last part of the paper present and discuss some of the most latest trends in application of stochastic local search algorithms in machine learning, data mining and some other areas of science and engineering. We conclude with a discussion on capabilities and limitations of stochastic local search algorithms.

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“…However, allowing hybridization can generate huge parameter spaces and generate algorithms with a complex, nested structure. For instance, the grammar based approach used in Pagnozzi and Stützle (2019) for the permutation flowshop problem with the makespan objective had 502 parameters.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the impact of grammar complexity in automatic algorithm design

Pagnozzi

Stützle

2020

Int Trans Operational Res

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Grammar-based automatic algorithm design has been shown to generate stochastic local search algorithms that compete with or outperform state-of-the-art methods. In such systems, algorithms are divided in components and a grammar is used to describe how to properly combine the components to create a working algorithm. In our approach, the grammar is converted in parameters and an automatic parameter configuration tool is used to find the best configuration. This approach allows to consider and hybridize different metaheuristic templates producing combinations never tested before, but this flexibility leads to a very large configuration space to explore. Is such complexity really needed to achieve state-of-the-art performance? In this paper, we investigate this question by creating grammars that allow the hybridization of stochastic local search algorithms at most two, one or zero times. We use these grammars to generate algorithms for the three most studied objectives of the permutation flowshop problem: makespan, total completion time and total tardiness. The generated algorithms are compared using benchmark sets from the literature as well as a quantitative measure of algorithm complexity using a metric based on concept directed acyclic graphs. The experiments show that our system tends to generate hybridized algorithms only when they can provide a substantial performance improvement. On the contrary, when such algorithms do not improve performance, the system generates simpler algorithms regardless of the grammar used.

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Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems

Cited by 39 publications

References 48 publications

Revisiting simulated annealing: A component-based analysis

Revisiting simulated annealing: A component-based analysis

Stochastic local search: a state-of-the-art review

Evaluating the impact of grammar complexity in automatic algorithm design

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