Michel Vasquez

A “Logic-Constrained” Knapsack Formulation and a Tabu Algorithm for the Daily Photograph Scheduling of an Earth Observation Satellite

The daily photograph scheduling problem of earth observation satellites such as Spot 5 consists of scheduling a subset of mono or stereo photographs from a given set of candidates to different cameras. The scheduling must maximize a profit function while satisfying a large number of constraints. In this paper, we first present a formulation of the problem as a generalized version of the well-known knapsack model, which includes large numbers of binary and ternary “logical” constraints. We then develop a tabu search algorithm which integrates some important features including an efficient neighborhood, a dynamic tabu tenure mechanism, techniques for constraint handling, intensification and diversification. Extensive experiments on a set of large and realistic benchmark instances show the effectiveness of this approach.

A Heuristic Approach for Antenna Positioning in Cellular Networks

The antenna-positioning problem concerns finding a set of sites for antennas from a set of pre-defined candidate sites, and for each selected site, to determine the number and types of antennas, as well as the associated values for each of the antenna parameters. All these choices must satisfy a set of imperative constraints and optimize a set of objectives. This paper presents a heuristic approach for tackling this complex and highly combinatorial problem. The proposed approach is composed of three phases: a constraint-based pre-processing phase to filter out bad configurations, an optimization phase using tabu search, and a post-optimization phase to improve solutions given by tabu search. To validate the approach, computational results are presented using large and realistic data sets.

Upper Bounds for the SPOT 5 Daily Photograph Scheduling Problem

This paper introduces tight upper bounds for the daily photograph scheduling problem of earth observation satellites. These bounds, which were unavailable until now, allow us to assess the quality of the heuristic solutions obtained previously. These bounds are obtained with a partition-based approach following the “divide and pas conquer” principle. Dynamic programming and tabu search are conjointly used in this approach. We present also simplex-based linear programming relaxation and a relaxed knapsack approach for the problem.

A multi-level search strategy for the 0-1 Multidimensional Knapsack Problem

We propose an exact method based on a multi-level search strategy for solving the 0-1 Multidimensional Knapsack Problem. Our search strategy is primarily based on the reduced costs of the non-basic variables of the LP-relaxation solution. Considering that the variables are sorted in decreasing order of their absolute reduced cost value, the top level branches of the search tree are enumerated following Resolution Search strategy, the middle level branches are enumerated following Branch & Bound strategy and the lower level branches are enumerated according to a simple Depth First Search enumeration strategy. Experimentally, this cooperative scheme is able to solve optimally large-scale strongly correlated 0-1 Multidimensional Knapsack Problem instances. The optimal values of all the 10 constraint, 500 variable instances and some of the 30 constraint, 250 variable instances of the OR-Library were found. These values were previously unknown.

A Hybrid Approach for SAT

Exploiting variable dependencies has been shown very useful in local search algorithms for SAT. In this paper, we extend the use of such dependencies by hybridizing a local search algorithm, Walksat, and the DPLL procedure, Satz. At each node reached in the DPLL search tree to a fixed depth, we construct the literal implication graph. Its strongly connected components are viewed as equivalency classes. Each one is substituted by a unique representative literal to reduce the constructed graph and the input formula. Finally, the implication dependencies are closed under transitivity. The resulted implications and equivalencies are exploited by Walksat at each node of the DPLL tree. Our approach is motivated by the power of the branching rule used in Satz that may provide a valid path to a solution, and generate more implications at deep nodes. Experimental results confirm the efficiency of our approach.

Bounding the optimum for the problem of scheduling the photographs of an Agile Earth Observing Satellite

The problem of managing an Agile Earth Observing Satellite consists of selecting and scheduling a subset of photographs among a set of candidate ones that satisfy imperative constraints and maximize a gain function. We propose a tabu search algorithm to solve this NP-hard problem. This one is formulated as a constrained optimization problem and involves stereoscopic and time window visibility constraints; and a convex evaluation function that increases its hardness. To obtain a wide-ranging and an efficient exploration of the search space, we sample it by consistent and saturated configurations. Our algorithm is also hybridized with a systematic search that uses partial enumerations. To increase the solution quality, we introduce and solve a secondary problem; the minimization of the sum of the transition durations between the acquisitions. Upper bounds are also calculated by a dynamic programming algorithm on a relaxed problem. The obtained results show the efficiency of our approach.

Une approche hybride pour le sac à dos multidimensionnel en variables 0–1

We present, in this article, a hybrid approach for solving the 0–1 multidimensional knapsack problem (MKP). This approach combines linear programming and Tabu search. The resulting algorithm improves on the best result on many well-known hard benchmarks.

The dynamic frequency assignment problem

In this paper, we consider a frequency assignment problem occurring in a military context. The main originality of the problem pertains to its dynamic dimension: new communications requiring frequency assignments need to be established throughout a battlefield deployment. The problem resolution framework decomposes into three phases: assignment of an initial kernel of communications, dynamic assignment of new communication links and a repair process when no assignment is possible. Different solution methods are proposed and extensive computational experiments are carried out on realistic instances.

Solving the selecting and scheduling satellite photographs problem with a consistent neighborhood heuristic

The problem of managing an Agile Earth Observing Satellite consists of selecting and scheduling a subset of photographs, among a set of candidate ones, satisfying imperative constraints and maximizing a gain function. In this paper, we propose a tabu search algorithm to solve the management problem of an Agile Earth Observing Satellite. This algorithm is an adaptation of CN-Tabu methodology working on a consistent neighborhood. Indeed, to obtain a wide-ranging and efficient exploration, the search space is sampled by consistent and saturated configurations. The consistency is maintained by constraint propagation and the saturation is a feature of the optimal solution. Furthermore, our tabu algorithm is hybridized with a systematic search, using partial enumerations, to solve several decisional problems. Moreover, for better resolution, a second objective problem, the minimization of the sum of transition durations between two image acquisitions, is introduced and tackled with a second tabu search algorithm.

Efficient Filtering and Tabu Search on a Consistent Neighbourhood for the Frequency Assignment Problem with Polarisation

This article presents a specific filtering algorithm for the Frequency Assignment Problem with Polarisation, which combines arc-consistency and path-inverse-consistency adapted to the specificities of the constraints. The effectiveness of this filtering algorithm enabled us to improve the Tabu Search on a Consistent Neighbourhood (CN-Tabu) using two different approaches. So, after a short recall of this general methodology and a presentation of its obtained results on the FAPP, we propose a behavioural study of the two approaches by comparing the results.