11 research outputs found

    Minimum Cost Homomorphisms to Reflexive Digraphs

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    For digraphs GG and HH, a homomorphism of GG to HH is a mapping $f:\ V(G)\dom V(H)suchthat such that uv\in A(G)implies implies f(u)f(v)\in A(H).Ifmoreovereachvertex. If moreover each vertex u \in V(G)isassociatedwithcosts is associated with costs c_i(u), i \in V(H),thenthecostofahomomorphism, then the cost of a homomorphism fis is \sum_{u\in V(G)}c_{f(u)}(u).Foreachfixeddigraph. For each fixed digraph H, the {\em minimum cost homomorphism problem} for H,denotedMinHOM(, denoted MinHOM(H),isthefollowingproblem.Givenaninputdigraph), is the following problem. Given an input digraph G,togetherwithcosts, together with costs c_i(u),, u\in V(G),, i\in V(H),andaninteger, and an integer k,decideif, decide if Gadmitsahomomorphismto admits a homomorphism to Hofcostnotexceeding of cost not exceeding k. We focus on the minimum cost homomorphism problem for {\em reflexive} digraphs H(everyvertexof (every vertex of Hhasaloop).ItisknownthattheproblemMinHOM( has a loop). It is known that the problem MinHOM(H)ispolynomialtimesolvableifthedigraph) is polynomial time solvable if the digraph H has a {\em Min-Max ordering}, i.e., if its vertices can be linearly ordered by <sothat so that i<j, s<rand and ir, js \in A(H)implythat imply that is \in A(H)and and jr \in A(H).WegiveaforbiddeninducedsubgraphcharacterizationofreflexivedigraphswithaMin−Maxordering;ourcharacterizationimpliesapolynomialtimetestfortheexistenceofaMin−Maxordering.Usingthischaracterization,weshowthatforareflexivedigraph. We give a forbidden induced subgraph characterization of reflexive digraphs with a Min-Max ordering; our characterization implies a polynomial time test for the existence of a Min-Max ordering. Using this characterization, we show that for a reflexive digraph H$ which does not admit a Min-Max ordering, the minimum cost homomorphism problem is NP-complete. Thus we obtain a full dichotomy classification of the complexity of minimum cost homomorphism problems for reflexive digraphs

    Minimum Cost Homomorphisms to Locally Semicomplete and Quasi-Transitive Digraphs

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    For digraphs GG and HH, a homomorphism of GG to HH is a mapping $f:\ V(G)\dom V(H)suchthat such that uv\in A(G)implies implies f(u)f(v)\in A(H).If,moreover,eachvertex. If, moreover, each vertex u \in V(G)isassociatedwithcosts is associated with costs c_i(u), i \in V(H),thenthecostofahomomorphism, then the cost of a homomorphism fis is \sum_{u\in V(G)}c_{f(u)}(u).Foreachfixeddigraph. For each fixed digraph H,theminimumcosthomomorphismproblemfor, the minimum cost homomorphism problem for H,denotedMinHOM(, denoted MinHOM(H),canbeformulatedasfollows:Givenaninputdigraph), can be formulated as follows: Given an input digraph G,togetherwithcosts, together with costs c_i(u),, u\in V(G),, i\in V(H),decidewhetherthereexistsahomomorphismof, decide whether there exists a homomorphism of Gto to H$ and, if one exists, to find one of minimum cost. Minimum cost homomorphism problems encompass (or are related to) many well studied optimization problems such as the minimum cost chromatic partition and repair analysis problems. We focus on the minimum cost homomorphism problem for locally semicomplete digraphs and quasi-transitive digraphs which are two well-known generalizations of tournaments. Using graph-theoretic characterization results for the two digraph classes, we obtain a full dichotomy classification of the complexity of minimum cost homomorphism problems for both classes

    A branch-and-price algorithm for a hierarchical crew scheduling problem.

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    We describe a real-life problem arising at a crane rental company. This problem is a generalization of the basic crew scheduling problem given in Mingozzi et al. and Beasley and Cao. We formulate the problem as an integer programming problem and establish ties with the integer multicommodity flow problem and the hierarchical interval scheduling problem. After establishing the complexity of the problem we propose a branch-and-price algorithm to solve it. We test this algorithm on a limited number of real-life instances.Scheduling;

    Departure Management with Robust Gate Allocation

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    International audienceThe Airport Collaborative Decision Making (A-CDM) concept yields concrete and promising solutions for airports, in terms of traffic punctuality and predictability, with possible delay, noise and pollution reduction. A key feature of A-CDM is the Departure Management (DMAN): runway takeoff sequences can be anticipated such that a significant part of the delay can be shifted at the gate, engines off, without penalizing the remaining traffic. During this process, an increase in the gate occupancy for delayed departures is unavoidable, therefore the airport layout must provide enough gates and their allocation must be robust enough w.r.t. departures delay. In this paper, we introduce a method to estimate the gate delays due to the DMAN pre-departure scheduling, then we propose a robust gate allocation algorithm and assess its performance with current and increased traffic at Paris-Charles-de-Gaulle international airport. Results show a significant reduction in the number of gate conflicts, when comparing such a robust gate allocation to current practice

    Interval Scheduling: A Survey

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    In interval scheduling, not only the processing times of the jobs but also their starting times are given. This article surveys the area of interval scheduling and presents proofs of results that have been known within the community for some time. We first review the complexity and approximability of different variants of interval scheduling problems. Next, we motivate the relevance of interval scheduling problems by providing an overview of applications that have appeared in literature. Finally, we focus on algorithmic results for two important variants of interval scheduling problems. In one variant we deal with nonidentical machines: instead of each machine being continuously available, there is a given interval for each machine in which it is available. In another variant, the machines are continuously available but they are ordered, and each job has a given "maximal" machine on which it can be processed. We investigate the complexity of these problems and describe algorithms for their solution

    A Unified Framework for Integer Programming Formulation of Graph Matching Problems

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    Graph theory has been a powerful tool in solving difficult and complex problems arising in all disciplines. In particular, graph matching is a classical problem in pattern analysis with enormous applications. Many graph problems have been formulated as a mathematical program then solved using exact, heuristic and/or approximated-guaranteed procedures. On the other hand, graph theory has been a powerful tool in visualizing and understanding of complex mathematical programming problems, especially integer programs. Formulating a graph problem as a natural integer program (IP) is often a challenging task. However, an IP formulation of the problem has many advantages. Several researchers have noted the need for natural IP formulation of graph theoretic problems. The aim of the present study is to provide a unified framework for IP formulation of graph matching problems. Although there are many surveys on graph matching problems, however, none is concerned with IP formulation. This paper is the first to provide a comprehensive IP formulation for such problems. The framework includes variety of graph optimization problems in the literature. While these problems have been studied by different research communities, however, the framework presented here helps to bring efforts from different disciplines to tackle such diverse and complex problems. We hope the present study can significantly help to simplify some of difficult problems arising in practice, especially in pattern analysis
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