A heuristic and meta-heuristic based on problem-specific knowledge for distributed blocking flow-shop scheduling problem with sequence-dependent setup times
F Zhao, H Bao, L Wang, T Xu, N Zhu - Engineering Applications of …, 2022 - Elsevier
The distributed production scenario with the sequence-dependent setup times (SDST)
widely exists in the modern manufacturing system. This paper investigates the distributed …
widely exists in the modern manufacturing system. This paper investigates the distributed …
Bilevel learning for large-scale flexible flow shop scheduling
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 …
problems within a limited time. In this paper, we propose a novel bilevel scheduler based on …
Dynamic matrix-based evolutionary algorithm for large-scale sparse multiobjective optimization problems
Multiobjective optimization problems exist widely in practical applications involving large-
scale decision variables and sparse Pareto optimal solutions. However, in terms of sparse …
scale decision variables and sparse Pareto optimal solutions. However, in terms of sparse …
Hybrid Monte Carlo tree search based multi-objective scheduling
As markets demand targeted products for highly differentiated use cases, the number of
variants in production increases, whilst the volume per variant decreases. Different product …
variants in production increases, whilst the volume per variant decreases. Different product …
Integrating Multi-Agent Systems in AI: A Framework Inspired by Physiology for Complex System Design
CH Chen, MF Shiu - 2024 - researchsquare.com
This study explores the integration of artificial intelligence (AI) through a Multi-Agent System
(MAS), utilizing autonomous networks to implement a novel framework demonstrated in a …
(MAS), utilizing autonomous networks to implement a novel framework demonstrated in a …