A Lookahead Behavior Model for Multi-Agent Hybrid Simulation

Yang, Mei; Peng, Yong; Ju, Ru-Sheng; Xu, Xiao; Yin, Quanjun; Ke-di, Huang

doi:10.3390/app7101095

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…Yang et al [3] used an operation loop with realistic link rules to model the cooperation relationships among weapons in the defense system. Wan et al [4] proposed a lookahead behavior model examining simulations. Lu and You [5] employed a new model with a route map and evaluated driven forces improvement of new technology to study real environment of defense skills.…”

Section: Introductionmentioning

confidence: 99%

Development of a Military Uniform Size System Using Hybrid Support Vector Clustering with a Genetic Algorithm

Chen

Yang

et al. 2019

Symmetry

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Military uniforms serve as an essential symbol for servicemen and an important image of national and military dignity. The current military uniform size system in Taiwan, which features various types of military uniforms based on the body sizes of servicemen, was formulated in 1986. This size classification system includes numerous groups and is too complex, leading to inventory overstock, increased inventory cost and warehouse staff workload, and a waste of national defense resources. This study used support vector clustering (SVC) with genetic algorithm (GA) models to improve the upper garment size system for uniforms. The SVC technique was employed to classify sizes, and the GA technique was used to determine optimal parameter values for the SVC model. This paper developed an upper garment size system that can increase the fit of uniforms to servicemen’s body sizes and reduce the number of size groups, thereby alleviating warehouse staff workload and inventory cost.

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Section: Introductionmentioning

confidence: 99%

Development of a Military Uniform Size System Using Hybrid Support Vector Clustering with a Genetic Algorithm

Chen

Yang

et al. 2019

Symmetry

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“…An output feedback controller is proposed that can stabilize non-autonomous hybrid systems by formulating the considered problem as a linear program. The second paper [8], authored by Yang, Peng, Ju, Xu, Yin, and Huang, is concerned with the efficiency improvement of multi-agent simulation. To address the problem of resynchronization interval selection and cyclic dependency, this paper presents a lookahead behavior model where a minimal safe time window is used to predict the interactions among implicit models.…”

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confidence: 99%

Special Issue on Modeling, Simulation, Operation and Control of Discrete Event Systems

Zhou

et al. 2018

Applied Sciences

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Information and computer technologies provide the spur to burgeoning man-made, highly automated systems. Nowadays, discrete event systems (DES), as a natural abstraction of various contemporary technological applications, include intelligent urban traffic systems, automated flexible manufacturing systems, computer networks, communication protocols, logistic systems, monitoring and control of large buildings, scientific and business workflows, distributed databases, and concurrent software systems. Their modeling, simulation, operation, scheduling and control are the primary issues to be investigated. It is of paramount significance to develop novel formal frameworks, analysis techniques, design tools, testing methods, and systematic control and optimization procedures for these kinds of man-made, highly complex systems. This is critical for their development and survivability [1][2][3][4][5][6].Focusing on supervisory control, deadlock analysis, scheduling, resource management, performance evaluation, system identification, fault diagnosis, and performance evaluation, as well as pertinent problems of DES, this special issue aims to make a timely collection of recent advances in the area. There were 77 manuscripts submitted to this special issue, and 19 papers were finally accepted for publication. The acceptance rate was 24.6%.The first paper [7], authored by Yao and Li, investigates the input-output finite time stabilization of time-varying impulsive positive hybrid systems based on finite state machines through the mode-dependent average dwell time technique. An output feedback controller is proposed that can stabilize non-autonomous hybrid systems by formulating the considered problem as a linear program. The second paper [8], authored by Yang, Peng, Ju, Xu, Yin, and Huang, is concerned with the efficiency improvement of multi-agent simulation. To address the problem of resynchronization interval selection and cyclic dependency, this paper presents a lookahead behavior model where a minimal safe time window is used to predict the interactions among implicit models. Consequently, the resynchronization interval can be efficiently determined.The third paper [9], authored by Kucharska, proposes a heuristic decision-making approach for an NP-hard scheduling problem based on an algebraic-logical meta-model. By constructing an acceptable solution only, it significantly reduces the calculation cost. A general algorithm is developed and applied to the scheduling problems of unrelated parallel machines with a deadline and machine setup time dependent on the process state. The fourth paper [10], authored by Choi, Seo, and Kim, deals with discrete event system simulation, aiming to improve simulation efficiency by using a multi-fidelity modeling framework, while keeping simulation accuracy loss minimized. A number of novel concepts, such as an interest region, a fidelity change condition, and a selection model, are defined and integrated into the framework.

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