Recently a logic programming language AC was proposed by Mellarkod et al. (2008) to integrate answer set programming (ASP) and constraint logic programming. Similarly, Gebser et al. (2009) proposed a CLINGCON language...
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Logic-based Benders decomposition can combine mixed integer programming and constraint programming to solve planning and scheduling problems much faster than either method alone. We find that a similar technique can b...
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Logic-based Benders decomposition can combine mixed integer programming and constraint programming to solve planning and scheduling problems much faster than either method alone. We find that a similar technique can be beneficial for solving pure scheduling problems as the problem size scales up. We solve single-facility non-preemptive scheduling problems with time windows and long time horizons. The Benders master problem assigns jobs to predefined segments of the time horizon, where the subproblem schedules them. In one version of the problem, jobs may not overlap the segment boundaries (which represent shutdown times, such as weekends), and in another version, there is no such restriction. The objective is to find feasible solutions, minimize makespan, or minimize total tardiness.
This paper proposes a constraint programming model for computing the finite horizon single-item inventory problem with stochastic demands in discrete time periods with service-level constraints under the non-stationar...
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This paper proposes a constraint programming model for computing the finite horizon single-item inventory problem with stochastic demands in discrete time periods with service-level constraints under the non-stationary version of the "periodic review, order-up-to-level" policy (i.e., non-stationary (R, S) or, simply (R, S,)). It is observed that the modeling process is more natural and the required number of variables is smaller compared to the MIP formulation of the same problem. The computational tests show that the CP approach is more tractable than the conventional MIP formulation. Two different domain reduction methods are proposed to improve the computational performance of solution algorithms. The numerical experiments confirmed the effectiveness of these methods. (C) 2007 Elsevier B.V. All rights reserved.
Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry, medicine, etc.) in order to help an...
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Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry, medicine, etc.) in order to help analysing such data and eliciting new knowledge from it. In addition to string processing bioinformatics is often identified with machine learning used for mining the large banks of bio-data available in electronic format, namely in a number of web servers. Nevertheless, there are opportunities of applying other computational techniques in some bioinformatics applications. In this paper, we report the application of constraint programming to address two structural bioinformatics problems, protein structure prediction and protein interaction (docking). The efficient application of constraint programming requires innovative modelling of these problems, as well as the development of advanced propagation techniques (e.g. global reasoning and propagation), which were adopted in Chemera, a system that is currently used to support biochemists in their research.
The novelty of this paper is to propose a parallel solver that mixes two constraint programming (CP) solvers, on top of our Bobpp framework, in order to have a parallel CP solver portfolio. The first chosen CP solver ...
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ISBN:
(纸本)9780769550947
The novelty of this paper is to propose a parallel solver that mixes two constraint programming (CP) solvers, on top of our Bobpp framework, in order to have a parallel CP solver portfolio. The first chosen CP solver is OR-tools which is an open source sequential solver. We propose an external OR-Tools parallelization (partitioning/migration/load balancing) on top of the Bobpp framework, where different instances of the OR-Tools solver are executed on different cores. The second chosen CP solver is Gecode that is also an open source sequential and parallel solver. The Gecode parallelization is internal in a sense that the parallel strategy is included in the library. The advantage of Gecode is that it can be easily interfaced with other software. Bobpp is a parallel framework that provides an interface between: Combinatorial Optimization problems or CP solvers and the parallel machines. Bobpp is designed to propose several parallelizations according to the parallel programming environment and the architecture of a machine. The performances of our solver portfolio are illustrated by solving CP problems modeled in Flat Zinc format.
Ground station scheduling problem arises in spacecraft operations and aims to allocate ground stations to spacecraft to make possible the communication between operations teams and spacecraft systems. The problem belo...
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Ground station scheduling problem arises in spacecraft operations and aims to allocate ground stations to spacecraft to make possible the communication between operations teams and spacecraft systems. The problem belongs to the family of satellite scheduling for the specific case of mapping communications to ground stations. The allocation of a ground station to a mission (e.g. telemetry, tracking information, etc.) has a high cost, and automation of the process provides many benefits not only in terms of management, but in economic terms as well. The problem is known for its high complexity as it is an over-constrained problem. In this paper, we present the resolution of the problem through Struggle Genetic Algorithms - a version of GAs that distinguishes for its efficiency in maintaining the diversity of the population during genetic evolution. We present some computational results obtained with Struggle GA using the STK simulation toolkit, which showed the efficiency of the method in solving the problem. (C) 2013 Elsevier Inc. All rights reserved.
Optimizing the daily operating room schedule can be problematic because of the many constraints that need to be taken into account, and solving this issue within a reasonable time span is difficult. The originality of...
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Optimizing the daily operating room schedule can be problematic because of the many constraints that need to be taken into account, and solving this issue within a reasonable time span is difficult. The originality of the present study is the consideration of the surgical team's wishes in the establishment of an operating room schedule. To resolve the operating room scheduling problem, we took advantage of the "expressive power" of the constraint programming paradigm to include multiple real-life constraints in our model, such as availability, staff preferences, and affinities among staff members. The aim of this research was to optimize use of the operating room by minimizing the makespan, minimizing overtime hours, and maximizing affinities among members of the surgical team. We developed a "generic" model that includes most of the problems encountered in the literature as well as constraints apparent in our hospital. The results achieved when using this model in a real-life situation are presented at the end of the paper. (C) 2012 Elsevier B.V. All rights reserved.
This paper provides a novel perspective in the Protein Structure Prediction (PSP) problem. The PSP problem focuses on determining putative 3D structures of a protein starting from its primary sequence. The proposed ap...
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ISBN:
(纸本)9780769551173
This paper provides a novel perspective in the Protein Structure Prediction (PSP) problem. The PSP problem focuses on determining putative 3D structures of a protein starting from its primary sequence. The proposed approach relies on a multi-agents approach, where concurrent agents explore the folding of different parts of a protein. The strength of the approach lies in the agents' ability to apply different types of knowledge (expressed in the form of declarative constraints) to prune the local space of folding alternatives. The paper demonstrates the suitability of a GPU approach to implement such multi-agent infrastructure, with significant improvements in speed and quality of solutions w.r.t. other methods (e. g., based on fragments assembly approaches).
Game theory is a highly successful paradigm for strategic decision making between multiple agents having conflicting objectives. Since a few years, games have been studied in a computational perspective, raising new i...
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ISBN:
(纸本)9781479929719
Game theory is a highly successful paradigm for strategic decision making between multiple agents having conflicting objectives. Since a few years, games have been studied in a computational perspective, raising new issues like complexity of equilibria or succinctness of representation. Indeed, the main representation for general games is still a n-dimensional matrix of exponential size called normal form. In this paper, we introduce the framework of constraint Games to model strategic interaction between players. A constraint Game is composed of a set of variables shared by all the players. Among these variables, each player owns a set of decision variables she can control and a constraint Optimization Problem defining her preferences. Since the preferences of a player depend on the decisions taken by the other players, each player may try to improve her position by choosing an assignment that optimizes her preferences. Pure Nash equilibria are situations in which no player may improve her preferences unilaterally. constraint Games are thus a generic tool to model general games and can be exponentially more succinct than their normal form. We show the practical utility of the framework by modelling a few realistic problems and we propose an algorithm based on tabu search to compute pure Nash equilibria in constraint games that outperforms the algorithms based on normal form. In addition, constraint Games raise some interesting research issues that deserve further attention.
Sometimes the business process model is not known completely, but a set of compliance rules can be used to describe the ordering and temporal relations between activities, incompatibilities, and existence dependencies...
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ISBN:
(纸本)9780769550855
Sometimes the business process model is not known completely, but a set of compliance rules can be used to describe the ordering and temporal relations between activities, incompatibilities, and existence dependencies in the process. The analysis of these compliance rules and the temporal events thrown during the execution of an instance, can be used to detect and diagnose a process behaviour that does not satisfy the expected behaviour. We propose to combine model-based diagnosis and constraint programming for the compliance violation analysis. This combination facilitates the diagnosis of discrepancies between the compliance rules and the events that the process generates as well as enables us to propose correct event time intervals to satisfy the compliance rules.
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