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A Knowledge-Based Two-Population Optimization Algorithm for Distributed Energy-Efficient Parallel Machines

Zixiao Pan, Deming Lei, Ling Wang

IEEE Transactions on Cybernetics

|October 29, 2020

Summary

This summary is machine-generated.

This study introduces a new algorithm for the distributed energy-efficient parallel machines scheduling problem (DEPMSP). The proposed knowledge-based two-population optimization (KTPO) algorithm effectively minimizes energy consumption and tardiness.

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Area of Science:

Operations Research
Computer Science
Industrial Engineering

Background:

Distributed scheduling and energy-efficient scheduling are critical research areas.
The integration of these problems, known as distributed energy-efficient scheduling, presents significant practical importance.
The distributed energy-efficient parallel machines scheduling problem (DEPMSP) remains an understudied area.

Purpose of the Study:

To address the novel distributed energy-efficient parallel machines scheduling problem (DEPMSP).
To develop an effective algorithm for minimizing both total energy consumption and total tardiness simultaneously.
To integrate factory and machine assignment subproblems into a unified framework.

Main Methods:

A knowledge-based two-population optimization (KTPO) algorithm is proposed.
The algorithm integrates factory and machine assignment using an extended machine assignment approach.
KTPO employs a hybrid approach combining nondominated sorting genetic algorithm-II and differential evolution, enhanced by knowledge-based local search operators.
Population initialization utilizes problem-specific knowledge-based and random heuristics.

Main Results:

Extensive simulations demonstrate the effectiveness of the KTPO algorithm.
Comparative analysis shows KTPO outperforms existing algorithms in solving DEPMSP.
Statistical analysis confirms the advantages of KTPO in minimizing energy consumption and tardiness.

Conclusions:

The proposed KTPO algorithm is effective for solving the distributed energy-efficient parallel machines scheduling problem (DEPMSP).
KTPO offers a viable solution for simultaneously minimizing energy consumption and tardiness in distributed manufacturing environments.
The integration of factory and machine assignment strategies enhances scheduling efficiency.