A memetic differential evolution algorithm for energy-efficient parallel machine scheduling

Wu, Xueqi; Che, Ada

doi:10.1016/j.omega.2018.01.001

Cited by 175 publications

(65 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Differential evolution (DE) [155] DE also employs mutation, crossover and selection to generate new candidates according to the difference between pairs of solutions used for searching a moving direction.…”

Section: Imitate the Foraging Behavior Of Bird Flockingmentioning

confidence: 99%

Local flexibility markets: Literature review on concepts, models and clearing methods

2020

View full text Add to dashboard Cite

 Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

show abstract

Section: Imitate the Foraging Behavior Of Bird Flockingmentioning

confidence: 99%

Local flexibility markets: Literature review on concepts, models and clearing methods

2020

View full text Add to dashboard Cite

show abstract

“…As the author described, these algorithms outperform existed methods in case of 120 jobs with 12 machines. In addition, a modified differential evolution algorithm was proposed to improve the consumption of energy problem for the UPSMPs [31]. The developed method characterized each job by determining speed vectors.…”

Section: Literature Reviewmentioning

confidence: 99%

Sine-Cosine Algorithm to Enhance Simulated Annealing for Unrelated Parallel Machine Scheduling with Setup Times

et al. 2019

View full text Add to dashboard Cite

This paper presents a hybrid method of Simulated Annealing (SA) algorithm and Sine Cosine Algorithm (SCA) to solve unrelated parallel machine scheduling problems (UPMSPs) with sequence-dependent and machine-dependent setup times. The proposed method, called SASCA, aims to improve the SA algorithm using the SCA as a local search method. The SCA provides a good tool for the SA to avoid getting stuck in a focal point and improving the convergence to an efficient solution. SASCA algorithm is used to solve UPMSPs by minimizing makespan. To evaluate the performance of SASCA, a set of experiments were performed using 30 tests for 4 problems. Moreover, the performance of the proposed method was compared with other meta-heuristic algorithms. The comparison results showed the superiority of SASCA over other methods in terms of performance dimensions.

show abstract

“…Li, et al [26] used a hybrid optimization approach to minimize carbon emissions. Wu and Che [27] proposed minimizing carbon emissions in parallel machines using the Memetic Differential Evolution algorithm. Batista Abikarram, et al [28] conducted minimizing carbon emissions in parallel machines.…”

Section: Nomenclature and Problem Definitionmentioning

confidence: 99%

An Effective Hybrid Sine Cosine Algorithm to Minimize Carbon Emission on Flow-shop Scheduling Sequence Dependent Setup

Utama

2019

JTI

View full text Add to dashboard Cite

Recently, carbon emissions have become a major environmental problem. In the industrial sector, carbon emissions account for half of the world's total carbon emissions. This article discusses the issue of scheduling Flow Shop Sequence Dependent Setup (FSSDS). It aims to minimize carbon emissions. The algorithm proposed is the Hybrid Sine Cosine Algorithm (HSCA) to solve FSSDS problems to reduce carbon emissions. We offered one of some search agents in the SCA use NEH. The algorithm is used for some test different jobs and machines. Several experiments were carried out to test the parameters and effectiveness of the algorithm. The parameters used in the trial are population and iteration. As a result, several parameters were proposed to HSCA to minimize carbon emissions. In the effectiveness test, the HSCA showed better performance compared to the simulated annealing and cross-entropy algorithm.

show abstract

A memetic differential evolution algorithm for energy-efficient parallel machine scheduling

Cited by 175 publications

References 44 publications

Local flexibility markets: Literature review on concepts, models and clearing methods

Local flexibility markets: Literature review on concepts, models and clearing methods

Sine-Cosine Algorithm to Enhance Simulated Annealing for Unrelated Parallel Machine Scheduling with Setup Times

An Effective Hybrid Sine Cosine Algorithm to Minimize Carbon Emission on Flow-shop Scheduling Sequence Dependent Setup

Contact Info

Product

Resources

About