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Production and operations management for intelligent manufacturing: A systematic literature review
In the context of Industry 4.0, the manufacturing sector is moving from automation towards
intelligence. The application of new generation information and communication …
intelligence. The application of new generation information and communication …
Evolutionary optimization methods for high-dimensional expensive problems: A survey
Evolutionary computation is a rapidly evolving field and the related algorithms have been
successfully used to solve various real-world optimization problems. The past decade has …
successfully used to solve various real-world optimization problems. The past decade has …
A reinforcement learning based RMOEA/D for bi-objective fuzzy flexible job shop scheduling
The flexible job shop scheduling problem (FJSP) is significant for realistic manufacturing.
However, the job processing time usually is uncertain and changeable during …
However, the job processing time usually is uncertain and changeable during …
Genetic algorithms and their applications
The first part of this chapter describes the foundation of genetic algorithms. It includes hybrid
genetic algorithms, adaptive genetic algorithms, and fuzzy logic controllers. After a short …
genetic algorithms, adaptive genetic algorithms, and fuzzy logic controllers. After a short …
A learning-based memetic algorithm for energy-efficient flexible job-shop scheduling with type-2 fuzzy processing time
Green flexible job-shop scheduling problem (FJSP) aims to improve profit and reduce
energy consumption for modern manufacturing. Meanwhile, FJSP with type-2 fuzzy …
energy consumption for modern manufacturing. Meanwhile, FJSP with type-2 fuzzy …
Solving fuzzy job-shop scheduling problem using DE algorithm improved by a selection mechanism
The emergence of fuzzy sets makes job-shop scheduling problem (JSSP) become better
aligned with the reality. This article addresses the JSSP with fuzzy execution time and fuzzy …
aligned with the reality. This article addresses the JSSP with fuzzy execution time and fuzzy …
Self-adaptive multi-objective evolutionary algorithm for flexible job shop scheduling with fuzzy processing time
With increasing environmental awareness and energy requirement, sustainable
manufacturing has attracted growing attention. Meanwhile, there is a high level of …
manufacturing has attracted growing attention. Meanwhile, there is a high level of …
Bi-population balancing multi-objective algorithm for fuzzy flexible job shop with energy and transportation
Flexible job shop scheduling problem (FJSP) is one of the challenging issues in industrial
systems. In this study, we propose a bi-population balancing multi-objective evolutionary …
systems. In this study, we propose a bi-population balancing multi-objective evolutionary …
Hybrid quantum particle swarm optimization and variable neighborhood search for flexible job-shop scheduling problem
The rise and integration of Industry 4.0 has led to a growing focus on the flexible job-shop
scheduling problem (FJSP). As an extension of the classic job-shop scheduling problem …
scheduling problem (FJSP). As an extension of the classic job-shop scheduling problem …
A hybrid iterated greedy algorithm for a crane transportation flexible job shop problem
JQ Li, Y Du, KZ Gao, PY Duan… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In this study, we propose an efficient optimization algorithm that is a hybrid of the iterated
greedy and simulated annealing algorithms (hereinafter, referred to as IGSA) to solve the …
greedy and simulated annealing algorithms (hereinafter, referred to as IGSA) to solve the …