Browsing by Author "Wang, Dingwei"
Now showing items 1-18 of 18
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Adaptive primal–dual genetic algorithms in dynamic environments.
Wang, Hongfeng; Yang, Shengxiang; Ip, W. H.; Wang, Dingwei (Article)Recently, there has been an increasing interest in applying genetic algorithms (GAs) in dynamic environments. Inspired by the complementary and dominance mechanisms in nature, a primal-dual GA (PDGA) has been proposed for ... -
Agent based evolutionary dynamic optimization.
Yan, Yang; Yang, Shengxiang; Wang, Dazhi; Wang, Dingwei (Book chapter) -
Compound particle swarm optimization in dynamic environments.
Liu, Lili; Wang, Dingwei; Yang, Shengxiang (Article)Adaptation to dynamic optimization problems is currently receiving a growing interest as one of the most important applications of evolutionary algorithms. In this paper, a compound particle swarm optimization (CPSO) is ... -
Constraint satisfaction adaptive neural network and efficient heuristics for job-shop scheduling
Yang, Shengxiang; Wang, Dingwei (Conference)An efficient constraint satisfaction based adaptive neural network and heuristics hybrid approach for job-shop scheduling is presented. The adaptive neural network has the property of adaptively adjusting its connection ... -
Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling
Wang, Dingwei; Yang, Shengxiang (Article)This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed ... -
Evolutionary algorithms in dynamic environments
Wang, Hongfeng; Wang, Dingwei; Yang, Shengxiang (Article)Evolutionary algorithms (EAs) are widely and often used for solving stationary optimization problems where the fitness landscape or objective function does not change during the course of computation. However, the environments ... -
Genetic algorithm and adaptive neural network hybrid method for job-shop scheduling problems
Yang, Shengxiang; Wang, Dingwei (Article)This paper proposes a hybrid method of genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) for solving job-shop scheduling problems. In the hybrid method GA is used to iterate for searching ... -
Genetic algorithm and neural network hybrid approach for job-shop scheduling
Zhao, Kai; Yang, Shengxiang; Wang, Dingwei (Conference)This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal ... -
An immune system based genetic algorithm using permutation-based dualism for dynamic traveling salesman problems.
Liu, Lili; Wang, Dingwei; Yang, Shengxiang (Article)In recent years, optimization in dynamic environments has attracted a growing interest from the genetic algorithm community due to the importance and practicability in real world applications. This paper proposes a new ... -
An improved constraint satisfaction adaptive neural network for job-shop scheduling.
Yang, Shengxiang; Wang, Dingwei; Chai, Tianyou; Kendall, Graham (Article)This paper presents an improved constraint satisfaction adaptive neural network for job-shop scheduling problems. The neural network is constructed based on the constraint conditions of a job-shop scheduling problem. Its ... -
A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems.
Wang, Hongfeng; Wang, Dingwei; Yang, Shengxiang (Article)Dynamic optimization problems challenge traditional evolutionary algorithms seriously since they, once converged, cannot adapt quickly to environmental changes. This paper investigates the application of memetic algorithms, ... -
A multi-agent based evolutionary algorithm in non-stationary environments.
Yan, Yang; Wang, Hongfeng; Wang, Dingwei; Yang, Shengxiang; Wang, Dazhi (Article)In this paper, a multi-agent based evolutionary algorithm (MAEA) is introduced to solve dynamic optimization problems. The agents simulate living organism features and co-evolve to find optimum. All agents live in a lattice ... -
A neural network and heuristics hybrid strategy for job-shop scheduling problem
Yang, Shengxiang; Wang, Dingwei (Article)A new efficient neural network and heuristics hybrid strategy for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving feasible ... -
A new adaptive neural network and heuristics hybrid approach for job-shop scheduling
Yang, Shengxiang; Wang, Dingwei (Article)A new adaptive neural network and heuristics hybrid approach for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving the feasible ... -
A particle swarm optimization based memetic algorithm for dynamic optimization problems.
Yang, Shengxiang; Wang, Hongfeng; Ip, W. H.; Wang, Dingwei (Article)Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm ... -
Solving optimization and scheduling problems with neural network methods
Yang, Shengxiang; Wang, Dingwei (Article)This paper briefly reviewed the applications of neural networks in optimization and scheduling problems. The background of combining neural networks with optimization and scheduling problems is first introduced, and ... -
Triggered memory-based swarm optimization in dynamic environments
Wang, Hongfeng; Wang, Dingwei; Yang, Shengxiang (Conference)In recent years, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are time-varying. In this paper, a triggered ... -
Using constraint satisfaction adaptive neural network and efficient heuristics for job-shop scheduling
Yang, Shengxiang; Wang, Dingwei (Article)This paper proposes a new adaptive neural network , based on constraint satisfaction, and efficient heuristics hybrid algorithm for job-shop scheduling. The neural network has the property of adapting its connection weights ...