Mathematical Models and a Constructive Heuristic for Finding Minimum Fundamental Cycle Bases
Maximization of distances of regular polygons on a circle
This paper presents the solution of a basic problem defined by J. Černý which solves a concrete everyday problem in railway and road transport (the problem of optimization of time-tables by some criteria).
Méthodes pour recenser toutes les cliques maximales et -maximales d’un graphe
Minimum convex-cost tension problems on series-parallel graphs
We present briefly some results we obtained with known methods to solve minimum cost tension problems, comparing their performance on non-specific graphs and on series-parallel graphs. These graphs are shown to be of interest to approximate many tension problems, like synchronization in hypermedia documents. We propose a new aggregation method to solve the minimum convex piecewise linear cost tension problem on series-parallel graphs in operations.
Minimum convex-cost tension problems on series-parallel graphs
We present briefly some results we obtained with known methods to solve minimum cost tension problems, comparing their performance on non-specific graphs and on series-parallel graphs. These graphs are shown to be of interest to approximate many tension problems, like synchronization in hypermedia documents. We propose a new aggregation method to solve the minimum convex piecewise linear cost tension problem on series-parallel graphs in O(m3) operations.
Minimum cut in directed planar networks
Minmax regret combinatorial optimization problems: an Algorithmic Perspective
Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have been developed over the last 40 years. In our paper we essentially discuss a particular uncertainty model associated with combinatorial optimization problems, developed in the 90's and broadly studied in the past years. This approach named minmax regret (in particular our emphasis is on the robust deviation criteria) is different from the classical approach for handling uncertainty, stochastic approach,...
Minmax regret combinatorial optimization problems: an Algorithmic Perspective
Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have been developed over the last 40 years. In our paper we essentially discuss a particular uncertainty model associated with combinatorial optimization problems, developed in the 90's and broadly studied in the past years. This approach named minmax regret (in particular our emphasis is on the robust deviation criteria) is different from the classical approach for handling uncertainty, stochastic approach,...
Modèle adaptant les politiques de personnel aux besoins prévisionnels
Modelling integer linear programs with Petri nets
Modelling integer linear programs with petri nets*
We show in this paper that timed Petri nets, with one resource shared by all the transitions, are directly connected to the modelling of integer linear programs (ILP). To an ILP can be automatically associated an equivalent Petri net. The optimal reachability delay is an optimal solution of the ILP. We show next that a net can model any ILP. I order to do this, we give a new sufficient reachability condition for the marking equation, which also holds for general Petri nets without timed transitions. ...
Multicriteria Optimum Path Problems
Multiperiod medians on networks
Multiple routing strategies in a labelled network
We present here models and algorithms for the construction of efficient path systems, robust to possible variations of the characteristics of the network. We propose some interpretations of these models and proceed to numerical experimentations of the related algorithms. We conclude with a discussion of the way those concepts may be applied to the design of a Public Transportation System.
Multiple Routing Strategies in a Labelled Network
We present here models and algorithms for the construction of efficient path systems, robust to possible variations of the characteristics of the network. We propose some interpretations of these models and proceed to numerical experimentations of the related algorithms. We conclude with a discussion of the way those concepts may be applied to the design of a Public Transportation System.