Recent advances in hybrid evolutionary algorithms for multiobjective manufacturing scheduling
In real manufacturing systems there are many combinatorial optimization problems (COP)
imposing on more complex issues with multiple objectives. However it is very difficult for …
imposing on more complex issues with multiple objectives. However it is very difficult for …
Multi-objective adaptive large neighborhood search for distributed reentrant permutation flow shop scheduling
AP Rifai, HT Nguyen, SZM Dawal - Applied Soft Computing, 2016 - Elsevier
Factory management plays an important role in improving the productivity and quality of
service in the production process. In particular, the distributed permutation flow shop …
service in the production process. In particular, the distributed permutation flow shop …
Agent-based approach integrating deep reinforcement learning and hybrid genetic algorithm for dynamic scheduling for Industry 3.5 smart production
CF Chien, YB Lan - Computers & Industrial Engineering, 2021 - Elsevier
Dynamic scheduling is crucial for semiconductor manufacturing as product-mix is increasing
with shortening product life cycle. However, the present problem is challenging owing to …
with shortening product life cycle. However, the present problem is challenging owing to …
Genetic algorithms in supply chain management: A critical analysis of the literature
Genetic algorithms (GAs) are perhaps the oldest and most frequently used search
techniques for dealing with complex and intricate real-life problems that are otherwise …
techniques for dealing with complex and intricate real-life problems that are otherwise …
Dynamic coordinated scheduling for supply chain under uncertain production time to empower smart production for Industry 3.5
To empower smart production for supply chain management, scheduling coordination and
integration between suppliers, manufacturers, distributors, and customers is becoming …
integration between suppliers, manufacturers, distributors, and customers is becoming …
Embedding ant system in genetic algorithm for re-entrant hybrid flow shop scheduling problems with time window constraints
This paper focuses on minimizing the makespan for a reentrant hybrid flow shop scheduling
problem with time window constraints (RHFSTW), which is often found in manufacturing …
problem with time window constraints (RHFSTW), which is often found in manufacturing …
A fuzzy logic-based hybrid estimation of distribution algorithm for distributed permutation flowshop scheduling problems under machine breakdown
As the research interest in distributed scheduling is growing, distributed permutation
flowshop scheduling problems (DPFSPs) have recently attracted an increasing attention …
flowshop scheduling problems (DPFSPs) have recently attracted an increasing attention …
Considering stockers in reentrant hybrid flow shop scheduling with limited buffer capacity
CC Lin, WY Liu, YH Chen - Computers & Industrial Engineering, 2020 - Elsevier
Diversification of products has increased the involvement of reentrant manufacturing
processes, in which a job returns multiple times to a machine at the preceding workflow …
processes, in which a job returns multiple times to a machine at the preceding workflow …
Multi-objective multi-population biased random-key genetic algorithm for the 3-D container loading problem
The container loading problem (CLP) has important industrial and commercial application
for global logistics and supply chain. Many algorithms have been proposed for solving the …
for global logistics and supply chain. Many algorithms have been proposed for solving the …
Bi-objective reentrant hybrid flowshop scheduling: an iterated Pareto greedy algorithm
The multi-objective reentrant hybrid flowshop scheduling problem (RHFSP) exhibits
significance in many industrial applications, but appears under-studied in the literature. In …
significance in many industrial applications, but appears under-studied in the literature. In …