A5001377691- Scheduling and Optimization Algorithms
- Advanced Manufacturing and Logistics Optimization
- Assembly Line Balancing Optimization
- Optimization and Search Problems
- Topological Materials and Phenomena
- Advanced Text Analysis Techniques
- Optimization and Packing Problems
- Metaheuristic Optimization Algorithms Research
- Graphene research and applications
- Auction Theory and Applications
- Opinion Dynamics and Social Influence
- Magnetic properties of thin films
- Iron-based superconductors research
- Complex Network Analysis Techniques
- 2D Materials and Applications
National Yang Ming Chiao Tung University
2011-2025
National Chin-Yi University of Technology
2023
National Penghu University of Science and Technology
2018
Feng Chia University
2007-2016
National Tsing Hua University
2013
Successful fabrication of α-FeTe/Bi 2 Te 3 provides a distinct platform from β-FeTe/Bi , enabling an exploration the interplay between magnetism and interface-induced superconductivity.
In this paper, we consider a permutation flowshop scheduling problem with deteriorating jobs. The objective is to minimize the total tardiness of all A branch-and-bound algorithm incorporating dominance property and lower bound developed. Furthermore, two metaheuristic algorithms, simulated annealing algorithm, particle swarm optimization method, are proposed. Finally, computational studies given.
Scheduling with two competing agents has become popular in recent years. Most of the research focused on single-machine problems. This article considers a parallel-machine problem, objective which is to minimize total completion time jobs from first agent given that maximum tardiness second cannot exceed an upper bound. The NP-hardness this problem also examined. A genetic algorithm equipped local search proposed for near-optimal solution. Computational experiments are conducted evaluate algorithm.
Many uncertainties arise during the manufacturing process, such as changes in working environment, traffic transportation delays, machine breakdowns, and worker performance instabilities. These factors can cause job processing times ready to change. In this study, we address a scheduling model for single where both release dates are scenario dependent. The objective is minimize total completion time across worst-case scenarios. Even without uncertainty factor, problem NP-hard. To solve it,...
This paper delves into the scheduling of two-machine flow-shop problem with step-learning, a scenario in which job processing times decrease if they commence after their learning dates. The objective is to optimize resource allocation and task sequencing ensure efficient time utilization timely completion all jobs, also known as makespan. identified established NP-hard due its reduction single machine for common date. To address this complexity, introduces an initial integer programming...
We consider a single-machine two-agent problem where the objective is to minimize weighted combination of total completion time and tardiness jobs from first agent given that no tardy are allowed for second agent. A branch-and-bound algorithm developed derive optimal sequence two simulated annealing heuristic algorithms proposed search near-optimal solutions. Computational experiments also conducted evaluate algorithms.
How to disseminate information or ideas through social network connection has received much attention in recent years. The core issue is find a seed set of initially active individuals that can maximize the influence spread. In this paper, we present comparative study on three basic algorithms for such issue. Experimental results show although genetic algorithm slightly better solution than other algorithms, it too time-consuming be cost-effective. Hence, our on-going work aimed at improving...