Review of job shop scheduling research and its new perspectives under Industry 4.0
Traditional job shop scheduling is concentrated on centralized scheduling or semi-
distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and …
distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and …
Application of grey wolf optimization for solving combinatorial problems: Job shop and flexible job shop scheduling cases
T Jiang, C Zhang - Ieee Access, 2018 - ieeexplore.ieee.org
Grey wolf optimization (GWO) algorithm is a new population-oriented intelligence algorithm,
which is originally proposed to solve continuous optimization problems inspired from the …
which is originally proposed to solve continuous optimization problems inspired from the …
Flexible job shop scheduling problem with reconfigurable machine tools: An improved differential evolution algorithm
Develo** reconfigurable machine tools (RMTs) has attracted increasing attention recently.
An RMT can be utilized as a group of machines, which can obtain different configurations to …
An RMT can be utilized as a group of machines, which can obtain different configurations to …
A hybrid differential evolution algorithm for flexible job shop scheduling with outsourcing operations and job priority constraints
H Li, X Wang, J Peng - Expert Systems with Applications, 2022 - Elsevier
Owing to the increasing complexity of products and the specialization of enterprises,
production outsourcing has become a common practice in industrial manufacturing …
production outsourcing has become a common practice in industrial manufacturing …
Beer froth artificial bee colony algorithm for job-shop scheduling problem
Job-shop scheduling problem (JSSP) is a vital combinatorial optimization problem in the
field of machine scheduling. The high complexity of JSSP is attracting researchers since the …
field of machine scheduling. The high complexity of JSSP is attracting researchers since the …
Evolutionary algorithm with individual-distribution search strategy and regression-classification surrogates for expensive optimization
Surrogate-assisted evolutionary algorithms (SAEAs) with prescreening model management
strategies show great potential in handling expensive optimization problems (EOPs) …
strategies show great potential in handling expensive optimization problems (EOPs) …
A two-stage differential biogeography-based optimization algorithm and its performance analysis
F Zhao, S Qin, Y Zhang, W Ma, C Zhang… - Expert Systems with …, 2019 - Elsevier
Biogeography-based optimization (BBO) has drawn a lot of attention as its outstanding
performance. However, same with certain typical swarm optimization algorithm, BBO …
performance. However, same with certain typical swarm optimization algorithm, BBO …
A hybrid algorithm based on self-adaptive gravitational search algorithm and differential evolution
F Zhao, F Xue, Y Zhang, W Ma, C Zhang… - Expert Systems with …, 2018 - Elsevier
Abstract The Gravitational Search Algorithm (GSA) has excellent performance in solving
various optimization problems. However, it has been demonstrated that GSA tends to trap …
various optimization problems. However, it has been demonstrated that GSA tends to trap …
Graph-based modeling in shop scheduling problems: Review and extensions
Graphs are powerful tools to model manufacturing systems and scheduling problems. The
complexity of these systems and their scheduling problems has been substantially …
complexity of these systems and their scheduling problems has been substantially …
Hybrid evolutionary optimisation with learning for production scheduling: state-of-the-art survey on algorithms and applications
Evolutionary Algorithms (EAs) has attracted significantly attention with respect to complexity
scheduling problems, which is referred to evolutionary scheduling. However, EAs differ in …
scheduling problems, which is referred to evolutionary scheduling. However, EAs differ in …