Container vessel stowage planning is a hard combinatorial optimization problem with both high economic and environmental impact. We have developed an approach that often is able to generate near-optimal plans for larg...
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Container vessel stowage planning is a hard combinatorial optimization problem with both high economic and environmental impact. We have developed an approach that often is able to generate near-optimal plans for large container vessels within a few minutes. It decomposes the problem into a master planning phase that distributes the containers to bay sections and a slot planning phase that assigns containers of each bay section to slots. In this paper, we focus on the slot planning phase of this approach and present a constraint programming and Integer programming model for stowing a set of containers in a single bay section. This so-called slot planning problem is NP-hard and often involves stowing several hundred containers. Using state-of-the-art constraint solvers and modeling techniques, however, we were able to solve 90% of 236 real instances from our industrial collaborator to optimality within 1 second. Thus, somewhat to our surprise, it is possible to solve most of these problems optimally within the time required for practical application. (C) 2012 Elsevier B.V. All rights reserved.
constraint programming is a powerful tool for modeling various problems in operations research. Its strength lies in the use of predicates, or global high-level constraints, on a few variables to efficiently model com...
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constraint programming is a powerful tool for modeling various problems in operations research. Its strength lies in the use of predicates, or global high-level constraints, on a few variables to efficiently model complex and varied problem structures. In this paper, we consider the predicate at-least. It bounds the number of variables in a set that may receive a specific value. This is a generalization of the standard logic condition expressed when the sum of binary variables is expressing a lower bound on the cardinality of a set. We have completely determined the convex hull representation of this predicate and provide a polynomial separation algorithm for inclusion in branch-and-bound integer programming software.
Network-level pavement maintenance programming is characterised by its high computational complexity. In this article, a novel modelling to solve this problem efficiently is proposed. In this modelling, careful care h...
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Network-level pavement maintenance programming is characterised by its high computational complexity. In this article, a novel modelling to solve this problem efficiently is proposed. In this modelling, careful care has been taken to reduce the search space and formulate the original problem as one of the well-known problems of the literature on mathematical optimisation. Efficient algorithms can therefore be used to find a solution. According to this approach, the maintenance programming problem is divided into two sub-problems: (i) the first performs a reduction of the search space by filtering road section maintenance alternatives based on technical criteria;(ii) the second computes a road network-level maintenance program by optimising efficiency subject to budget constraints. The section-level filtering of alternatives is modelled as a constraint satisfaction problem and solved using appropriate constraint satisfaction algorithms. The network-level maintenance programming is modelled as a generalised assignment problem, whose resolution is well documented in the literature on optimisation. This approach has shown to be very effective, with strong computational performances for different road network sizes.
In 2004, Jean-Francois Puget presented [2] an analysis of the "simplicity of Use" of constraint programming from which he articulated a series of challenges to make constraint programming systems accessible ...
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We study transformational computational creativity in the context of writing songs and describe an implemented system that is able to modify its own goals and operation. With this, we contribute to three aspects of co...
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We study transformational computational creativity in the context of writing songs and describe an implemented system that is able to modify its own goals and operation. With this, we contribute to three aspects of computational creativity and song generation: (1) Application-wise, songs are an interesting and challenging target for creativity, as they require the production of complementary music and lyrics. (2) Technically, we approach the problem of creativity and song generation using constraint programming. We show how constraints can be used declaratively to define a search space of songs so that a standard constraint solver can then be used to generate songs. (3) Conceptually, we describe a concrete architecture for transformational creativity where the creative (song writing) system has some responsibility for setting its own search space and goals. In the proposed architecture, a meta-level control component does this transparently by manipulating the constraints at runtime based on self-reflection of the system. Empirical experiments suggest the system is able to create songs according to its own taste.
This paper introduces a hybrid algorithm for the dynamic dial-a-ride problem in which service requests arrive in real time. The hybrid algorithm combines an exact constraint programming algorithm and a tabu search heu...
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This paper introduces a hybrid algorithm for the dynamic dial-a-ride problem in which service requests arrive in real time. The hybrid algorithm combines an exact constraint programming algorithm and a tabu search heuristic. An important component of the tabu search heuristic consists of three scheduling procedures that are executed sequentially. Experiments show that the constraint programming algorithm is sometimes able to accept or reject incoming requests, and that the hybrid method outperforms each of the two algorithms when they are executed alone.
The quorumcast routing problem is a generalization of multicasting which arises in many distributed applications. It consists of finding a minimum cost tree that spans the source node r and at least q out of m specifi...
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The quorumcast routing problem is a generalization of multicasting which arises in many distributed applications. It consists of finding a minimum cost tree that spans the source node r and at least q out of m specified nodes on a given undirected weighted graph. This paper proposes a complete and an incomplete approach, both based on the same constraint programming (CP) model, but with two different specific search heuristics based on shortest paths. Experimental results show the efficiency of the two proposed approaches. Our complete approach (CP model + complete search) is better than the state of the art complete algorithm and our incomplete approach (CP model + incomplete search) is better than the state of the art incomplete algorithm. Moreover, the proposed complete search is better than the standard First-Fail search in the same CP model.
An intelligent robotic system must be capable of making the best decision at any given moment. The criteria for which task is "best" can be derived by performance metrics as well as the ability for it to sat...
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An intelligent robotic system must be capable of making the best decision at any given moment. The criteria for which task is "best" can be derived by performance metrics as well as the ability for it to satisfy all constraints upon the robot and its mission. constraints may exist based on safety, reliability, accuracy, etc. This paper presents a decision framework capable of assisting a robotic system to select a task that satisfies all constraints as well as is optimized based upon one or more performance criteria. The framework models this decision process as a constraint satisfaction problem using techniques and algorithms from constraint programming and constraint optimization in order to provide a solution in real-time. This paper presents this framework and initial results provided through two demonstrations. The first utilizes simulation to provide an initial proof of concept, and the second, a security robot demonstration, is performed using a physical robot.
In this article, we consider the problem of planning preventive maintenance of railway signals in Denmark. This case is particularly relevant as the entire railway signalling system is currently being upgraded to the ...
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In this article, we consider the problem of planning preventive maintenance of railway signals in Denmark. This case is particularly relevant as the entire railway signalling system is currently being upgraded to the new European Railway Traffic Management System (ERTMS) standard. This upgrade has significant implications for signal maintenance scheduling in the system. We formulate the problem as a multi-depot vehicle routing and scheduling problem with time windows and synchronisation constraints, in a multi-day time schedule. The requirement that some tasks require the simultaneous presence of more than one engineer means that task synchronisation must be considered. A multi-stage constructive framework is proposed, which first distributes maintenance tasks using a clustering formulation. Following this, a constraint programming (CP) based approach is used to generate feasible monthly plans for large instances of practical interest. Experimental results indicate that the proposed framework can generate feasible solutions and schedule a monthly plan of up to 1000 tasks for eight crew members, in a reasonable amount of computational time.
Graph labeling problems have been widely studied in the last decades and have a vast area of application. In this work, we study the recently introduced S-labeling problem, in which the nodes get labeled using labels ...
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Graph labeling problems have been widely studied in the last decades and have a vast area of application. In this work, we study the recently introduced S-labeling problem, in which the nodes get labeled using labels from 1 to vertical bar V vertical bar and for each edge the contribution to the objective function, called S-labeling number of the graph, is the minimum label of its end-nodes. The goal is to find a labeling with minimum value. The problem is NP-hard for planar subcubic graphs, although for many other graph classes the complexity status is still unknown. In this paper, we present different algorithmic approaches for tackling this problem: We develop an exact solution framework based on Mixed-Integer programming (MIP) which is enhanced with valid inequalities, starting and primal heuristics and specialized branching rules. We show that our MIP formulation has no integrality gap for paths, cycles and perfect n-ary trees, and, to the best of our knowledge, we give the first polynomial-time algorithm for the problem on n-ary trees as well as a closed formula for the 5-labeling number for such trees. Moreover, we also present a Lagrangian heuristic and a constraint programming approach. A computational study is carried out in order to (i) investigate if there may be other special graph classes, where our MIP formulation has no integrality gap, and (ii) assess the effectiveness of the proposed solution approaches for solving the problem on a dataset consisting of general graphs. (C) 2019 Elsevier Ltd. All rights reserved.
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