A review of green shop scheduling problem
M Li, GG Wang - Information Sciences, 2022 - Elsevier
The manufacturing industry directly reflects the productivity level of a country and plays an
important role in economic and social development. However, with the development of the …
important role in economic and social development. However, with the development of the …
A self-learning discrete jaya algorithm for multiobjective energy-efficient distributed no-idle flow-shop scheduling problem in heterogeneous factory system
F Zhao, R Ma, L Wang - IEEE Transactions on Cybernetics, 2021 - ieeexplore.ieee.org
In this study, a self-learning discrete Jaya algorithm (SD-Jaya) is proposed to address the
energy-efficient distributed no-idle flow-shop scheduling problem (FSP) in a heterogeneous …
energy-efficient distributed no-idle flow-shop scheduling problem (FSP) in a heterogeneous …
Energy-efficient scheduling in job shop manufacturing systems: a literature review
Energy efficiency has become a major concern for manufacturing companies not only due to
environmental concerns and stringent regulations, but also due to large and incremental …
environmental concerns and stringent regulations, but also due to large and incremental …
A two-stage cooperative evolutionary algorithm with problem-specific knowledge for energy-efficient scheduling of no-wait flow-shop problem
Green scheduling in the manufacturing industry has attracted increasing attention in
academic research and industrial applications with a focus on energy saving. As a typical …
academic research and industrial applications with a focus on energy saving. As a typical …
Solving biobjective distributed flow-shop scheduling problems with lot-streaming using an improved Jaya algorithm
A distributed flow-shop scheduling problem with lot-streaming that considers completion
time and total energy consumption is addressed. It requires to optimally assign jobs to …
time and total energy consumption is addressed. It requires to optimally assign jobs to …
An effective hybrid collaborative algorithm for energy-efficient distributed permutation flow-shop inverse scheduling
J Mou, P Duan, L Gao, X Liu, J Li - Future Generation Computer Systems, 2022 - Elsevier
Distributed scheduling problem, a novel model of intelligent manufacturing, urgently needs
new scheduling methods to meet the dynamic market demand. The inverse scheduling in a …
new scheduling methods to meet the dynamic market demand. The inverse scheduling in a …
Distributed scheduling problems in intelligent manufacturing systems
Currently, manufacturing enterprises face increasingly fierce market competition due to the
various demands of customers and the rapid development of economic globalization …
various demands of customers and the rapid development of economic globalization …
A cooperative memetic algorithm with learning-based agent for energy-aware distributed hybrid flow-shop scheduling
With increasing environmental awareness and energy requirement, sustainable
manufacturing has attracted growing attention. Meanwhile, distributed manufacturing …
manufacturing has attracted growing attention. Meanwhile, distributed manufacturing …
A cooperative memetic algorithm with feedback for the energy-aware distributed flow-shops with flexible assembly scheduling
With economic globalization and increasingly concerned sustainable manufacturing, energy-
aware distributed scheduling and flexible assembly are significant to optimize global supply …
aware distributed scheduling and flexible assembly are significant to optimize global supply …
A reinforcement learning driven cooperative meta-heuristic algorithm for energy-efficient distributed no-wait flow-shop scheduling with sequence-dependent setup …
Green manufacturing has attracted increasing attention under the background of carbon
peaking and carbon neutrality. Distributed production has widely existed in various …
peaking and carbon neutrality. Distributed production has widely existed in various …