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Bayesian estimation of the mean holding time in average semi-Markov control processes

J. Adolfo Minjárez-Sosa, José A. Montoya (2015)

Applicationes Mathematicae

We consider semi-Markov control models with Borel state and action spaces, possibly unbounded costs, and holding times with a generalized exponential distribution with unknown mean θ. Assuming that such a distribution does not depend on the state-action pairs, we introduce a Bayesian estimation procedure for θ, which combined with a variant of the vanishing discount factor approach yields average cost optimal policies.

Bayesian parameter estimation and adaptive control of Markov processes with time-averaged cost

V. Borkar, S. Associate (1998)

Applicationes Mathematicae

This paper considers Bayesian parameter estimation and an associated adaptive control scheme for controlled Markov chains and diffusions with time-averaged cost. Asymptotic behaviour of the posterior law of the parameter given the observed trajectory is analyzed. This analysis suggests a "cost-biased" estimation scheme and associated self-tuning adaptive control. This is shown to be asymptotically optimal in the almost sure sense.

Belief functions induced by multimodal probability density functions, an application to the search and rescue problem

P.-E. Doré, A. Martin, I. Abi-Zeid, A.-L. Jousselme, P. Maupin (2010)

RAIRO - Operations Research - Recherche Opérationnelle

In this paper, we propose a new method to generate a continuous belief functions from a multimodal probability distribution function defined over a continuous domain. We generalize Smets' approach in the sense that focal elements of the resulting continuous belief function can be disjoint sets of the extended real space of dimension n. We then derive the continuous belief function from multimodal probability density functions using the least commitment principle. We illustrate the approach on two...

Belief functions induced by multimodal probability density functions, an application to the search and rescue problem

P.-E. Doré, A. Martin, I. Abi-Zeid, A.-L. Jousselme, P. Maupin (2011)

RAIRO - Operations Research

In this paper, we propose a new method to generate a continuous belief functions from a multimodal probability distribution function defined over a continuous domain. We generalize Smets' approach in the sense that focal elements of the resulting continuous belief function can be disjoint sets of the extended real space of dimension n. We then derive the continuous belief function from multimodal probability density functions using the least commitment principle. We illustrate the approach on two...

Bemerkungen zum Verfahren der koordinatenweisen Suche

Dieter Oelschlägel, Herbert Süsse (1981)

Aplikace matematiky

In der vorliegenden Arbeit wird das Verfahren der koordinatenweisen Suche mit Hilfe der Intervallarithmetik realisiert. Dadurch ist es möglich, bei speziellen nichtlinearen Optimierungsproblemen alle auftretenden Fehlerarten zu erfaßen, einschliesslich eingangsbedingter Fehler. Vor- und Nachteile werden erläutert sowie Testbeispiele angegeben.

Bi-directional nearness in a network by AHP (Analytic Hierarchy Process) and ANP (Analytic Network Process)

Kazutomo Nishizawa (2010)

RAIRO - Operations Research

In this paper we study bi-directional nearness in a network based on AHP (Analytic Hierarchy Process) and ANP (Analytic Network Process). Usually we use forward (one-dimensional) direction nearness based on Euclidean distance. Even if the nearest point to i is point j, the nearest point to j is not necessarily point i. Sowe propose the concept of bi-directional nearness defined by AHP'ssynthesizing of weights “for” direction and “from” direction. This concept of distance is a relative distance...

Binary integer programming solution for troubleshooting with dependent actions

Václav Lín (2017)

Kybernetika

We deal with a sequencing problem that arises when there are multiple repair actions available to fix a broken man-made system and the true cause of the system failure is uncertain. The system is formally described by a probabilistic model, and it is to be repaired by a sequence of troubleshooting actions designed to identify the cause of the malfunction and fix the system. The task is to find a course of repair with minimal expected cost. We propose a binary integer programming formulation for...

Bootstrap clustering for graph partitioning

Philippe Gambette, Alain Guénoche (2011)

RAIRO - Operations Research - Recherche Opérationnelle

Given a simple undirected weighted or unweighted graph, we try to cluster the vertex set into communities and also to quantify the robustness of these clusters. For that task, we propose a new method, called bootstrap clustering which consists in (i) defining a new clustering algorithm for graphs, (ii) building a set of graphs similar to the initial one, (iii) applying the clustering method to each of them, making a profile (set) of partitions, (iv) computing a consensus partition for this profile,...

Bootstrap clustering for graph partitioning∗

Philippe Gambette, Alain Guénoche (2012)

RAIRO - Operations Research

Given a simple undirected weighted or unweighted graph, we try to cluster the vertex set into communities and also to quantify the robustness of these clusters. For that task, we propose a new method, called bootstrap clustering which consists in (i) defining a new clustering algorithm for graphs, (ii) building a set of graphs similar to the initial one, (iii) applying the clustering method to each of them, making a profile (set) of partitions, (iv) computing a consensus partition for this profile,...

Bottleneck capacity expansion problems with general budget constraints

Rainer E. Burkard, Bettina Klinz, Jianzhong Zhang (2001)

RAIRO - Operations Research - Recherche Opérationnelle

This paper presents a unified approach for bottleneck capacity expansion problems. In the bottleneck capacity expansion problem, BCEP, we are given a finite ground set E , a family ℱ of feasible subsets of E and a nonnegative real capacity c ^ e for all e ∈ E . Moreover, we are given monotone increasing cost functions f e for increasing the capacity of the elements e ∈ E as well as a budget B . The task is to determine new capacities c e ≥ c ^ e such that the objective function given by max F ∈ ℱ min e ∈ F c e is maximized under the side constraint...

Bottleneck Capacity Expansion Problems with General Budget Constraints

Rainer E. Burkard, Bettina Klinz, Jianzhong Zhang (2010)

RAIRO - Operations Research

This paper presents a unified approach for bottleneck capacity expansion problems. In the bottleneck capacity expansion problem, BCEP, we are given a finite ground set E, a family F of feasible subsets of E and a nonnegative real capacity ĉe for all e ∈ E. Moreover, we are given monotone increasing cost functions fe for increasing the capacity of the elements e ∈ E as well as a budget B. The task is to determine new capacities ce ≥ ĉe such that the objective function given by maxF∈Fmine∈Fce...

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