Multi-Objective Production and Scheduling Optimization of Offshore Wind Turbine Steel Pipe Piles Based on Improved Hesitant Fuzzy Method

Author:

Wang Weihan123ORCID,Xiao Jinchao23ORCID,Feng Dongying2,Wei Sanxi2,Wang Zhongze234

Affiliation:

1. College of Chemical Process Automation, Shenyang University of Technology, Shengyang 110870, China

2. Guangzhou Institute of Industrial Intelligence, Guangzhou 511458, China

3. Shenyang Institute of Automation, Chinese Academy of Sciences, Shengyang 110016, China

4. University of Chinese Academy of Sciences, Beijing 100049, China

Abstract

This paper investigates the multi-objective optimization problem in the production of offshore wind turbine steel pipe piles (OWTSPP). Considering the particularity of the steel pipe pile production process, it is divided into a flexible flow shop scheduling (FFSS) stage and an open parallel shop scheduling (OPSS) stage, respectively. Mathematical models are established for each stage, and the critical path and production time information are obtained using a disjunctive graph model. Due to the inability of existing empirical scheduling methods to balance production goals, an improved Pythagorean hesitant fuzzy method (IPHFM) is proposed to solve the multi-objective optimization problem in steel pipe pile production. Specifically, the maximum completion time, machine total load, and total completion time are taken as optimization objectives. The improved Lagrange multiplier method with penalty terms is used to handle the constraints and objective functions, and a Lagrange objective function is generated. Then, the Lagrange objective function matrix is obtained by normalization and same-scale processing, and an algorithm is designed to obtain the Pareto front solution set. Finally, this paper compares the optimal scheduling plans under the empirical scheduling method and the improved method. The results show that the improved method can significantly improve production efficiency in both small-scale and large-scale production, with improvements of 15.7% and 22.16%, respectively.

Funder

National Key Research and Development Program

Nansha District Science and Technology Project, Guangzhou, Guangdong Province, China

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

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