An adaptive CP method for TSP solving

M. Sellmann showed that CP-based Lagrangian relaxation gave good results but the interactions between the two techniques were quite dicult to understand. There are two main reasons for this: the best multipliers do not lead to the best ltering and each ltering disrupts the Lagrangian multiplier problem (LMP) to be solved. As the resolution of the TSP in CP is mainly based on a Lagrangian relaxation, we propose to study in detail these interactions for this particular problem. This article experimentally conrms the above statements and shows that it is very dicult to establish any relationship between ltering and the method used to solve the LMP in practice. Thus, it seems very dicult to select a priori the best method suited for a given instance. We propose to use a multi-armed bandit algorithm to nd the best possible method to use. The experimental results show the advantages of our approach

A study on contextual influences on automatic playlist continuation

Recommender systems still mainly base their reasoning on pairwise interactions or information on individual entities, like item attributes or ratings, without properly evaluating the multiple dimensions of the recommendation problem. However, in many cases, like in music, items are rarely consumed in isolation, thus users rather need a set of items, selected to work well together, serving a specific purpose, while having some cognitive properties as a whole, related to their perception of quality and satisfaction, under given circumstances. In this paper, we introduce the term of playlist concept in order to capture the implicit characteristics of joint music item selections, related to their context, scope and general perception by the users. Although playlist consumptions may be associated with contextual attributes, these may be of various types, differently influencing users' preferences, based on their character and emotional state, therefore differently reflected on their final selections. We highlight on the use of this term in HybA, our hybrid recommender system, to identify clusters of similar playlists able to capture inherit characteristics and semantic properties, not explicitly described in them. The experimental results presented, show that this conceptual clustering results in playlist continuations of improved quality, compared to using explicit contextual parameters, or the commonly used collaborative filtering technique.Peer ReviewedPostprint (published version

Effective Heuristics to Solve Pickup and Delivery Problems with Time Windows

Pickup and delivery problem with time windows (PDP-TW) is a challenging scheduling problem for which each delivery is coupled with a pickup request. Metaheuristic search techniques like the tabu search have been used to solve PDP-TW. In this paper, we investigated a min-conflicts based micro-genetic algorithm combining some interesting construction heuristic, namely the Align-Fold or Boomerang, and repair heuristics including a new Swap operator and a modified billiard operator to effectively solve PDD-TW. Our results compared favorably against those of a tabu-embedded metaheuristic search on a set of modified Solomon's test cases. More importantly, our proposed heuristics can easily be integrated into many search schemes for solving other complex scheduling problems.published_or_final_versio

Effective Heuristics to Solve Pickup and Delivery Problems with Time Windows

Pickup and delivery problem with time windows (PDP-TW) is a challenging scheduling problem for which each delivery is coupled with a pickup request. Metaheuristic search techniques like the tabu search have been used to solve PDP-TW. In this paper, we investigated a min-conflicts based micro-genetic algorithm combining some interesting construction heuristic, namely the Align-Fold or Boomerang, and repair heuristics including a new Swap operator and a modified billiard operator to effectively solve PDD-TW. Our results compared favorably against those of a tabu-embedded metaheuristic search on a set of modified Solomon's test cases. More importantly, our proposed heuristics can easily be integrated into many search schemes for solving other complex scheduling problems.published_or_final_versio

Distributed splitting of constraint satisfaction problems

Constraint propagation aims to reduce a constraint satisfaction problem into an equivalent but simpler one. However, constraint propagation must be interleaved with a splitting mechanism in order to compose a complete solver. In~cite{monfroy:sac2000 a framework for constraint propagation based on a control-driven coordination model was presented. In this paper we extend this framework in order to integrate a distributed splitting mechanism. This technique has three main advantages: 1),in a single distributed and generic framework, propagation and splitting can be interleaved in order to realize complete distributed solvers, 2), by changing only one agent, we can perform different kinds of search, and 3), splitting of variables can be dynamically triggered before the fixed point of a propagation is reached

Global constraints as graph properties on structured network of elementary constraints of the same type

This report introduces a classification scheme for the global constraints. This classification is based on four basic ingredients from which one can generate almost all existing global constraints and come up with new interesting constraints. Global constraints are defined in a very concise way, in term of graph properties that have to hold, where the graph is a structured network of same elementary constraints. Since this classification is based on the internal structure of the global constraints it is also a strong hint for the pruning algorithms of the global constraints

Improving PARMA Trailing

Taylor introduced a variable binding scheme for logic variables in his PARMA system, that uses cycles of bindings rather than the linear chains of bindings used in the standard WAM representation. Both the HAL and dProlog languages make use of the PARMA representation in their Herbrand constraint solvers. Unfortunately, PARMA's trailing scheme is considerably more expensive in both time and space consumption. The aim of this paper is to present several techniques that lower the cost. First, we introduce a trailing analysis for HAL using the classic PARMA trailing scheme that detects and eliminates unnecessary trailings. The analysis, whose accuracy comes from HAL's determinism and mode declarations, has been integrated in the HAL compiler and is shown to produce space improvements as well as speed improvements. Second, we explain how to modify the classic PARMA trailing scheme to halve its trailing cost. This technique is illustrated and evaluated both in the context of dProlog and HAL. Finally, we explain the modifications needed by the trailing analysis in order to be combined with our modified PARMA trailing scheme. Empirical evidence shows that the combination is more effective than any of the techniques when used in isolation. To appear in Theory and Practice of Logic Programming.Comment: 36 pages, 7 figures, 8 table

Estimer le nombre de solutions des contraintes de cardinalité grâce à leur décomposition range et roots

National audienceEn programmation par contraintes, le choix d’une heuristique de recherche plutôt qu’une autre dépend souvent du problème. Cependant il existe des heuristiques génériques utilisant plutôt des indicateurs sur la structure combinatoire du problème. Les heuristiques "Counting- Based", introduites par Pesant et al., font des choix basés sur une estimation du nombre de solutions restantes dans tel ou tel sous-arbre de l’arbre de recherche. Un inconvénient de ces heuristiques est qu’elles nécessitent des algorithmes de dénombrement spécifiques à chaque contrainte. Cette étude s’intéresse aux contraintes de cardinalité, dont alldifferent, atmost, nvalue, etc... Nous proposons une méthode de comptage de solutions pour les contraintes range et roots, introduites par Bessiere et al. Grâce à la décomposition des contraintes de cardinalité en contraintes range et roots, nous dérivons une méthode systématique de dénombrement de solutions pour la plupart de ces contraintes