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Articles 1 - 11 of 11
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen
Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen
Journal of System Simulation
Abstract: Reinforcement Learning (RL) achieves lower time response and better model generalization in Job Shop Scheduling Problem (JSSP). To explain the current overall research status of JSSP based on RL, summarize the current scheduling framework based on RL, and lay the foundation for follow-up research, the backgrounds of JSSP and RL are introduced. Two simulation techniques commonly used in JSSP are analyzed and two commonly used frameworks for RL to solve JSSP are given. In addition, some existing challenges are pointed out, and related research progress is introduced from three aspects: direct scheduling, feature representation-based scheduling, and parameter search-based scheduling.
Study On Hand Gesture Recognition And Portfolio Optimization Model Based On Svm, Zhiwei Cai, Shuyan Wu, Junfeng Song
Study On Hand Gesture Recognition And Portfolio Optimization Model Based On Svm, Zhiwei Cai, Shuyan Wu, Junfeng Song
Journal of System Simulation
Abstract: Hand gesture recognition was researched. The idea of extracting related features was proposed by using SVM algorithm in machine learning domain, and combination optimization method was used, which consists of ANN, HMM and DTW, to do hand gesture recognition. The experimental results show that portfolio optimization model based gesture recognition method has high accuracy and is very effective.
Combinatorial Optimization Of Resolution Level In Three-Dimensional Visualization, Yanyang Zeng, Zhenhai Yu, Weidong Liu
Combinatorial Optimization Of Resolution Level In Three-Dimensional Visualization, Yanyang Zeng, Zhenhai Yu, Weidong Liu
Journal of System Simulation
Abstract: In the process of developing three-dimensional visualization, it is necessary to select and adjust the combined solutions of the resolution hierarchy of multiple models. If only by artificial attempting will lead to the more times of iteration and lower design efficiency, therefore, a method, combinatorial optimization of models' resolution level, is proposed. Image information entropy is introduced for evaluating the image quality of the scene. According to the assessed value of visual effects and it is provided to the above method based on particle swarm optimization (PSO), the models with the resolution hierarchy can be matched and reorganized. Through …
Novel Hierarchical Level Of Detail Combinatorial Optimization Method For Large-Scale 3d Scene, Che Li, Fengju Kang, Xueli Hou
Novel Hierarchical Level Of Detail Combinatorial Optimization Method For Large-Scale 3d Scene, Che Li, Fengju Kang, Xueli Hou
Journal of System Simulation
Abstract: The traditional design process of large-scale 3D scene is cumbersome and lengthy and fail to provide ideal scene rendering effect. Aiming at this problem, a feedback mechanism based combinatorial optimization of level of detail (LOD) model for large-scale 3D scene was proposed. Through analyzing the influence of observation distance, moving speed and other factors on visual perception, the mathematical model of visual sensitivity was established. By the frame rate and visualization effect feedback, invoking the model level selection criterion to adjust the model's LOD level, and eventually an optimal scene model combination solution could be obtained. Experimental results demonstrate …
Combinatorial Optimization Of 3d Visualization Simulation Based On Automatic-Correction, Yanyang Zeng, Qingqing Pei, Fengju Kang
Combinatorial Optimization Of 3d Visualization Simulation Based On Automatic-Correction, Yanyang Zeng, Qingqing Pei, Fengju Kang
Journal of System Simulation
Abstract: In order to enhance the visual simulation results, developers often need to combine and optimize the fine expression of the above entities, terrain and physical field by the individual experience under conditions of limited computer resources. The iterative process of debugging cycle is long, and it is difficult to solve the contradiction between good fidelity and real-time. So, cybernetics ideas, and proposes semi/fully automatic correction technology were introduced, which is composed of discrete multi-resolution representation of the three-dimensional model, assessment of visual effects and intelligent optimization, providing a decision support method for three-dimensional visual development. The method was applied …
Particle Swarm Ant Colony Optimization Algorithm For Solving Circle Permutation Problem, Xiaoping Xu, Qiuqiu Zhu, Wang Feng
Particle Swarm Ant Colony Optimization Algorithm For Solving Circle Permutation Problem, Xiaoping Xu, Qiuqiu Zhu, Wang Feng
Journal of System Simulation
Abstract: A particle swarm ant colony optimization algorithm of solving circle permutation problem was proposed. Based on the basis of analyzing relationship between circular permutation problem and traveling salesman problem, circular permutation problem was translated into traveling salesman problem, and it was further transformed into an optimization problem. In order to further improve the performance of the algorithm, here, four kinds of new scheme were proposed to solve circular permutation problem based on particle swarm ant colony optimization algorithm. In the simulation experiments, compared with the existing algorithm, the simulation results show that the proposed method is reasonable and feasible. …
Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir
Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir
Research Collection School Of Computing and Information Systems
Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …
Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau
Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …
Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau
Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We study the problem of optimizing the trajectories of agents moving over a network given their preferences over which nodes to visit subject to operational constraints on the network. In our running example, a theme park manager optimizes which attractions to include in a day-pass to maximize the pass’s appeal to visitors while keeping operational costs within budget. The first challenge in this combinatorial optimization problem is that it involves quantities (expected visit frequencies of each attraction) that cannot be expressed analytically, for which we use the Sample Average Approximation. The second challenge is that while sampling is typically done …
Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir
Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir
Research Collection School Of Computing and Information Systems
Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …
A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Xiaomin Jia, Wee Chong Wan
A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Xiaomin Jia, Wee Chong Wan
Research Collection School Of Computing and Information Systems
Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a well- designed set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that …