Pub Date : 2016-04-03DOI: 10.1109/WODES.2016.7497848
Y. Khazaeni, C. Cassandras
We consider event-driven methods in a general framework for the control and optimization of multi-agent systems, viewing them as stochastic hybrid systems. Such systems often have feasible realizations in which the events needed to excite an on-line event-driven controller cannot occur, rendering the use of such controllers ineffective. We show that this commonly happens in environments which contain discrete points of interest which the agents must visit. To address this problem in event-driven gradient-based optimization problems, we propose a new metric for the objective function which creates a potential field guaranteeing non-zero gradient values when no events are present and which results in eventual event excitation. We apply this approach to the class of cooperative multi-agent data collection problems using the event-driven Infinitesimal Perturbation Analysis (IPA) methodology and include numerical examples illustrating its effectiveness.
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Pub Date : 2016-01-14DOI: 10.1109/WODES.2016.7497837
Jianfeng Mao, C. Cassandras
We approach a class of discrete event simulation-based optimization problems using optimality in probability, an approach which yields what is termed a “champion solution”. Compared to the traditional optimality in expectation, this approach favors the solution whose actual performance is more likely better than that of any other solution; this is an effective alternative to the traditional optimality sense, especially when facing a dynamic and nonstationary environment. Moreover, using optimality in probability is computationally promising for a class of discrete event simulation-based optimization problems, since it can reduce computational complexity by orders of magnitude compared to general simulation-based optimization methods using optimality in expectation. Accordingly, we have developed an “Omega Median Algorithm” in order to effectively obtain the champion solution and to fully utilize the efficiency of well-developed off-line algorithms to further facilitate timely decision making. An inventory control problem with nonstationary demand is included to illustrate and interpret the use of the Omega Median Algorithm, whose performance is tested using simulations.
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Pub Date : 1900-01-01DOI: 10.1109/WODES.2016.7497831
R. Malik, Marcelo Teixeira
This paper proposes an algorithm for the synthesis of modular supervisors using extended finite-state machines, i.e., state machines with variables and guards on the transitions. Synthesis is performed by iteratively selecting components from a synchronous composition until a least restrictive controllable solution is obtained. This method is usually faster and produces smaller supervisors than standard monolithic synthesis, while offering the modelling benefits of variables. An example of manufacturing system control illustrates the approach.
{"title":"Modular supervisor synthesis for extended finite-state machines subject to controllability","authors":"R. Malik, Marcelo Teixeira","doi":"10.1109/WODES.2016.7497831","DOIUrl":"https://doi.org/10.1109/WODES.2016.7497831","url":null,"abstract":"This paper proposes an algorithm for the synthesis of modular supervisors using extended finite-state machines, i.e., state machines with variables and guards on the transitions. Synthesis is performed by iteratively selecting components from a synchronous composition until a least restrictive controllable solution is obtained. This method is usually faster and produces smaller supervisors than standard monolithic synthesis, while offering the modelling benefits of variables. An example of manufacturing system control illustrates the approach.","PeriodicalId":268613,"journal":{"name":"2016 13th International Workshop on Discrete Event Systems (WODES)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123987377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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