A5062451644- Multi-Criteria Decision Making
- Quality Function Deployment in Product Design
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Advanced Multi-Objective Optimization Algorithms
- Optimization and Mathematical Programming
- Vehicle Routing Optimization Methods
- Optimization and Packing Problems
- Value Engineering and Management
- Industrial Vision Systems and Defect Detection
- Advanced Measurement and Detection Methods
- Grey System Theory Applications
- Advanced Manufacturing and Logistics Optimization
Northwestern Polytechnical University
2013-2016
As the preference of design maker (DM) is always ambiguous, we have to face many multiple criteria decision-making (MCDM) problems with interval numbers in our daily life. Though there been some methods applied solve this sort problem, it complex comprehend and sometimes difficult implement. The calculation processes are ineffective when a new alternative added or removed. In view weakness like this, paper presents method based on TOPSIS response surface (RSM) for MCDM numbers, RSM-TOPSIS-IN...
This paper presents a novel biologically inspired metaheuristic algorithm called seven‐spot ladybird optimization (SLO). The SLO is by recent discoveries on the foraging behavior of ladybird. In this paper, performance compared with that genetic algorithm, particle swarm optimization, and artificial bee colony algorithms using five numerical benchmark functions multimodality. results show has ability to find best solution comparatively small population size suitable for solving problems...
Circles packing problem with equilibrium constraints is difficult to solve due its NP-hard nature. Aiming at this problem, three swarm intelligence algorithms are employed problem. Particle Swarm Optimization and Ant Colony has been used for the circular constraints. In paper, Artificial Bee Algorithm (ABC) presented. Then we compare performances of well-known (PSO, ACO, ABC) The results experiment show that ABC comparatively satisfying because stability applicability.
Increasing attention is being paid to solving engineering design optimization problems which are generally nonlinear and constrained.In this paper, the Seven-spot Ladybird Optimization (SLO) algorithm developed obtain solution of such problems.This paper presents basic concepts main steps SLO demonstrates its efficiency.The performance compared with some popular meta-heuristic algorithms by using four different dimensional classical benchmark functions.The simulation results indicate that...