source data for article entitled "multi-objective parallel variable neighborhood search for energy consumption scheduling in blocking flow shops"

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Abstract 

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A multi-objective parallel variable neighborhood search (MPVNS) algorithm is proposed for solving the multi-objective blocking flow shop scheduling problem. The MPVNS is compared with non-dominated sorting genetic algorithm (NSGA-II) and bi-objective multi-start simulated annealing algorithm (BMSA). This data provide the original results obtained by the three algorithms, which are compared in a research paper entitled "Multi-objective parallel variable neighborhood search for energy consumption scheduling in blocking flow shops".

Instructions: 

file folder named "1-MPVNS results" includes the original results of the MPVNS algorithm.

file folder named "2-BMSA results" includes the original results of the BMSA algorithm.

file folder named "3-NSGAII- results" includes the original results of the NSGAII algorithm.

file folder named "4-non-dominated solution sets obtained by 1-3" includes the non-dominated solutions of each algorithm and the net non-dominated front of each instance.

file folder named "5-results obtained by 4" includes the computed Set Coverage and Hypervolume results obtained by the data in file folder named "4-non-dominated solution sets obtained by 1-3".

Comments

this source data can possible serve as reference resources for future research
attempts

Submitted by Guanlong Deng on Sat, 10/06/2018 - 13:40