A Differential Evolution Algorithm for the Permutation Flowshop Scheduling Problem with Total Flow Time Criterion

Santucci, Valentino; Baioletti, Marco; Milani, Alfredo

doi:10.1007/978-3-319-10762-2_16

Cited by 23 publications

(13 citation statements)

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“…Differential Evolution for Permutations (DEP) algorithm has been successfully proposed in [5] for the Permutation Flowshop Scheduling Problem (PFSP), a combinatorial problem that share with LOP the same representation of solutions as permutations.…”

Section: Differential Evolution For Per-mutationsmentioning

confidence: 99%

“…For each population individual πi, a mutant permutation νi is generated according to νi = πr 0 • F π −1 r 2 • πr 1 where πr 0 , πr 1 , πr 2 are three distinct randomly selected elements of the current population, • is the permutation composition operator and is the operator, described in [5], which allows to compute the scaled difference.…”

Section: Differential Evolution For Per-mutationsmentioning

confidence: 99%

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An Algebraic Differential Evolution for the Linear Ordering Problem

Santucci

Baioletti

Milani

2015

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

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In this paper we propose a discrete algebraic-based Differential Evolution for the Linear Ordering Problem (LOP). The search space of LOP is composed by permutations of objects, thus it is possible to use some group theoretical concepts and methods. Indeed, the proposed algorithm is a fully discrete Differential Evolution scheme and has been designed by exploiting the group structure of LOP solutions in order to mimic the classical Differential Evolution behavior observed in continuous numerical spaces. The performances have been evaluated over widely known LOP benchmark suites and have been compared to the state-of-the-art results.

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Section: Differential Evolution For Per-mutationsmentioning

confidence: 99%

Section: Differential Evolution For Per-mutationsmentioning

confidence: 99%

An Algebraic Differential Evolution for the Linear Ordering Problem

Santucci

Baioletti

Milani

2015

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation

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“…The mutation operator used is the same of DEP [6]. It produces a mutant ν i for each population element π i using some algebraic concepts related to the symmetric group of permutations.…”

Section: Differential Mutationmentioning

confidence: 99%

“…DEP is a discrete differential evolution algorithm which directly operates on the permutations space and hence is well suited for permutation optimization problems like PFSP. Indeed, in [6] and in [5], it was shown that DEP reaches state-of-the-art results with respect to total flowtime and makespan single objective optimization. Here, DEP has been extended in order to handle multi-objective problems.…”

Section: Introductionmentioning

confidence: 97%

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A discrete differential evolution algorithm for multi-objective permutation flowshop scheduling

Baioletti

Milani

Santucci

2016

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Real-world versions of the permutation flowshop scheduling problem (PFSP) have a variety of objective criteria to be optimized simultaneously. Multi-objective PFSP is also a relevant combinatorial multi-objective optimization problem. In this paper we propose a multiobjective evolutionary algorithm for PFSPs by extending the previously proposed discrete differential evolution scheme for single-objective PF-SPs. The novelties of this proposal reside on the management of the evolved Pareto front and on the selection operator. A preliminary experimental evaluation has been conducted on three bi-objective PFSPs resulting from all the possible bi-objective combinations of the criteria makespan, total flowtime and total tardiness.

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