Problem-specific knowledge MOEA/D for energy-efficient scheduling of distributed permutation flow shop in heterogeneous factories

C Luo, W Gong, R Li, C Lu - Engineering Applications of Artificial …, 2023 - Elsevier
With the development of the global economy and the enhancement of environmental
awareness, energy-efficient permutation flow shop scheduling gets more attention …

Fleet and charging infrastructure decisions for fast-charging city electric bus service

N Guschinsky, MY Kovalyov, B Rozin… - Computers & Operations …, 2021 - Elsevier
Decision aspects concerning the introduction of fast-charging city electric buses are studied
in this paper. The main studied problem consists of determining a fleet of electric buses and …

Deterministic constructive vN-NEH+ algorithm to solve permutation flow shop scheduling problem with makespan criterion

R Puka, I Skalna, J Duda, A Stawowy - Computers & Operations Research, 2024 - Elsevier
Scheduling jobs in a permutation flow shop (PFS) environment is one of the most studied
problems in scheduling theory and practice. In this paper, we propose a new efficient …

Bilevel learning for large-scale flexible flow shop scheduling

L Li, X Fu, HL Zhen, M Yuan, J Wang, J Lu… - Computers & Industrial …, 2022 - Elsevier
Many industrial practitioners are facing the challenge of solving large-scale scheduling
problems within a limited time. In this paper, we propose a novel bilevel scheduler based on …

N-list-enhanced heuristic for distributed three-stage assembly permutation flow shop scheduling

KC Ying, P Pourhejazy, PJ Fu - Annals of Operations Research, 2023 - Springer
Abstract System-wide optimization of distributed manufacturing operations enables process
improvement beyond the standalone and individual optimality norms. This study addresses …

[HTML][HTML] An Optimization Method for Green Permutation Flow Shop Scheduling Based on Deep Reinforcement Learning and MOEA/D

Y Lu, Y Yuan, A Sitahong, Y Chao, Y Wang - Machines, 2024 - mdpi.com
This paper addresses the green permutation flow shop scheduling problem (GPFSP) with
energy consumption consideration, aiming to minimize the maximum completion time and …

[HTML][HTML] Reinforcement learning-based alpha-list iterated greedy for production scheduling

KC Ying, P Pourhejazy, SH Cheng - Intelligent Systems with Applications, 2024 - Elsevier
Metaheuristics can benefit from analyzing patterns and regularities in data to perform more
effective searches in the solution space. In line with the emerging trend in the optimization …

Deterministic method for input sequence modification in NEH-based algorithms

R Puka, I Skalna, B Łamasz, J Duda, A Stawowy - IEEE Access, 2024 - ieeexplore.ieee.org
Scheduling of production jobs falls into the area of planning, which, according to Henri
Fayol's conception, is one of the basic functions of management. The permutation flow-shop …

New measures of algorithms quality for permutation flow-shop scheduling problem

R Puka, I Skalna, T Derlecki - 2023 18th Conference on …, 2023 - ieeexplore.ieee.org
The permutation flow-shop scheduling problem (PFSP) is an important problem in
production industry. The problem has been a subject of many research and various …

Swap method to improve n-neh+ algorithm

R Puka, I Skalna, B Łamasz - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
The NEH heuristic is commonly regarded as the best constructive heuristic for solving the
permutation flow-shop scheduling problem (PFSP) with the makespan criterion. Since its …