Semiconductor final testing scheduling using Q-learning based hyper-heuristic
J Lin, YY Li, HB Song - Expert Systems with Applications, 2022 - Elsevier
Semiconductor final testing scheduling problem (SFTSP) has extensively been studied in
advanced manufacturing and intelligent scheduling fields. This paper presents a Q-learning …
advanced manufacturing and intelligent scheduling fields. This paper presents a Q-learning …
Scheduling semiconductor testing facility by using cuckoo search algorithm with reinforcement learning and surrogate modeling
ZC Cao, CR Lin, MC Zhou… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
A semiconductor final testing scheduling problem with multiresource constraints is
considered in this paper, which is proved to be NP-hard. To minimize the makespan for this …
considered in this paper, which is proved to be NP-hard. To minimize the makespan for this …
A novel fruit fly optimization algorithm for the semiconductor final testing scheduling problem
In this paper, a novel fruit fly optimization algorithm (nFOA) is proposed to solve the
semiconductor final testing scheduling problem (SFTSP). First, a new encoding scheme is …
semiconductor final testing scheduling problem (SFTSP). First, a new encoding scheme is …
A review of machine efficiency in mass customization
CD James, S Mondal - Benchmarking: An International Journal, 2019 - emerald.com
Purpose The purpose of this paper is to address the gap between definition and practical
aspects of production efficiency in mass customization (MC). The paper summarizes all …
aspects of production efficiency in mass customization (MC). The paper summarizes all …
Learning-based grey wolf optimizer for stochastic flexible job shop scheduling
C Lin, Z Cao, MC Zhou - IEEE Transactions on Automation …, 2022 - ieeexplore.ieee.org
This work considers a stochastic flexible job shop scheduling with limited extra resources
and machine-dependent setup time in a semiconductor manufacturing environment, which …
and machine-dependent setup time in a semiconductor manufacturing environment, which …
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 …
An effective invasive weed optimization algorithm for scheduling semiconductor final testing problem
HY Sang, PY Duan, JQ Li - Swarm and Evolutionary Computation, 2018 - Elsevier
In this paper, we address a semiconductor final testing problem from the semiconductor
manufacturing process. We aim to determine both the assignment of machines and the …
manufacturing process. We aim to determine both the assignment of machines and the …
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 …
Knowledge-enhanced multidimensional estimation of distribution hyper-heuristic evolutionary algorithm for semiconductor final testing scheduling problem
ZQ Zhang, XH Qiu, B Qian, R Hu, L Wang… - Expert Systems with …, 2025 - Elsevier
The semiconductor final test scheduling problem (SFTSP), recognized as a crucial
bottleneck in the semiconductor production process, holds immense significance for …
bottleneck in the semiconductor production process, holds immense significance for …
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 …