T his article considers the overall crew management problem arising from the daily operation of an urban transit bus company that serves the metropolitan area of the city of Belo Horizonte, Brazil.. Due to its intrins...
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T his article considers the overall crew management problem arising from the daily operation of an urban transit bus company that serves the metropolitan area of the city of Belo Horizonte, Brazil.. Due to its intrinsic complexity, the problem is divided in two distinct subproblems: crew scheduling and crew rostering. We have investigated each of these problems using mathematical programming (MP) and constraint logic programming (CLP) approaches. In addition, we developed hybrid column generation algorithms for solving these problems, combining MP and CLP The hybrid algorithms always performed better, when obtaining optimal solutions, than the two previous isolated approaches. In particular, they proved to be much faster for the scheduling problem. All the proposed algorithms have been implemented and tested over real-world data obtained from the aforementioned company. The coefficient matrix of the linear program associated with some instances of the scheduling problem contains tens of millions of columns;this number is even larger for the rostering problem. The analysis of our experiments indicates that it was possible to find high-quality, and many times optimal, solutions that were suitable for the company's needs. These solutions were obtained within reasonable computational times on a desktop PC.
This paper presents a hybrid algorithm that combines local search and constraint programming techniques to solve a network routing problem. The problem considered is that of routing traffic demands from a set of reque...
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This paper presents a hybrid algorithm that combines local search and constraint programming techniques to solve a network routing problem. The problem considered is that of routing traffic demands from a set of requests over a network with limited capacity so as to minimise the cost of any unrouted demands. The hybridisation is twofold: pure local search is used to find a good cost bound for a subsequent branch-and-bound optimisation phase, with local search again applied at the nodes of the branch-and-bound search tree. constraint propagation occurs in the search tree to reduce the domains of the decision variables, using a set of constraints that are independent of the action of local search at the nodes. In contrast to previous constraint programming/local search hybridisations, here local search is used to satisfy the hard problem constraints, while optimisation is handled in the framework of constraint programming. The resulting algorithm is incomplete, but is shown to compare favourably with a complete approach to this problem.
In this paper, we introduce a meeting scheduling system based on open constraint programming (OCP) paradigm. OCP is an extension to constraint logic programming (CLP), where a server capable of executing constraint lo...
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This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for...
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This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for locating radio network controllers (RNCs) from a set of pre-defined candidate sites, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize an objective function. This problem is NP-hard and consequently cannot be practically solved by exact methods for real size networks. Thus, this paper proposes a hybrid search strategy for tackling this complex and combinatorial optimization problem. The proposed hybrid search strategy is composed of three phases: A constraint satisfaction method with an embedded problem-specific goal which guides the search for a good initial solution, an optimization phase using local search algorithms, such as tabu algorithm, and a postoptimization phase to improve solutions from the second phase by using a constraint optimization procedure. Computational results show that the proposed search strategy and the model are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within 5.77% to 7.48% of the lower bounds.
Starting from a need and a set of functional requirements (FRs), a designer is often perplexed to assess the potential of a given concept to fit these requirements. He is even more perplexed when several concepts are ...
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ISBN:
(纸本)079184742X
Starting from a need and a set of functional requirements (FRs), a designer is often perplexed to assess the potential of a given concept to fit these requirements. He is even more perplexed when several concepts are candidates. This paper proposes a definition of a concept in a practical way as a parameterized model linking a set of design variables (DVs) to a set of performance variables (PVs). This set of PVs is supposed to be the same for any concept candidate to fulfill a need. This is why our model propose to "plug" a card of FRs into candidate concepts in order to lead concurrent reasonings on competing concepts until one or several of them appear to be of poor interest. The plugging mechanism is implemented by constraint programming techniques (evolved interval arithmetics) that immediately contract the performance and design variable domains to provide an outer approximation of the solution (or design) space. Two sets of comparison operators between solution spaces are proposed: operators for comparing the relative potential of two concepts submitted to the same FRs, and operators for comparing two Successive stages of solution spaces of a given concept. These last operators provide the way to tackle the robustness of design decision making under uncertainty. All the mentioned features: Plugging mechanism, contraction of domains and design space representation, comparison operators and robustness considerations have been experimented on an example of a pair of candidate concepts of truss structures.
The analysis of biochemical networks consists in studying the interactions between biological entities cooperating in complex cellular processes. To facilitate the expression of analyses and their computation, we intr...
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ISBN:
(纸本)3540250794
The analysis of biochemical networks consists in studying the interactions between biological entities cooperating in complex cellular processes. To facilitate the expression of analyses and their computation, we introduced CP(BioNet), a constraint programming framework for the analysis of biochemical networks. An Oz-Mozart prototype of CP(BioNet) is described. This prototype consists of the implementation of a new kind of domain variables, graph domain variables, and the implementation of constraint propagators for constraints over graph-domain variables. These new variables and constraints are implemented in Oz and they can then be used like other domain variables in the Oz-Mozart platform. An implementation of a path constraint propagator is described in depth and constrained path finding tests are analysed to assess the tractability of our approach. Finally, an alternative Oz-Mozart data-structure for the graph-domain variables is presented and compared to the first one.
This paper presents a hybrid algorithm that combines local search and constraint programming techniques to solve a network routing problem. The problem considered is that of routing traffic demands from a set of reque...
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ISBN:
(纸本)1577352017
This paper presents a hybrid algorithm that combines local search and constraint programming techniques to solve a network routing problem. The problem considered is that of routing traffic demands from a set of requests over a network with limited capacity so as to minimise the cost of any unrouted demands. The hybridisation is twofold: pure local search is used to find a good cost bound for a subsequent branch-and-bound optimisation phase, with local search again applied at the nodes of the branch-and-bound search tree. constraint propagation occurs in the search tree to reduce the domains of the decision variables, using a set of constraints that are independent of the action of local search at the nodes. In contrast to previous constraint programming/local search hybridisations, here local search is used to satisfy the hard problem constraints, while optimisation is handled in the framework of constraint programming. The resulting algorithm is incomplete, but is shown to compare favourably with a complete approach to this problem.
In the context of web service procurement (WSP), temporal-awareness refers to managing service demands and offers which are subject to validity periods, i.e. their evaluation depends not only on quality of service (Qo...
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ISBN:
(纸本)3540308172
In the context of web service procurement (WSP), temporal-awareness refers to managing service demands and offers which are subject to validity periods, i.e. their evaluation depends not only on quality of service (QoS) values but also on time. For example, the QoS of some web services can be considered critical in working hours (9:00 to 17:00 from Monday to Friday) and irrelevant at any other moment. Until now, the expressiveness of such temporal-aware specifications has been quite limited. As far as we know, most proposals have considered validity periods to be composed of a single temporal interval. Other proposals, which could allow more expressive time-dependent specifications, have not performed a detailed study about all the underlying complexities of such approach, in spite of the fact that dealing with complex expressions on temporality is not a trivial task at all. As a matter of fact, it requires a special design of the so-called procurement tasks (consistency and conformance checking, and optimal selection). In this paper, we present a constraint-based approach to temporal-aware WSR Using constraints allows a great deal of expressiveness, so that not only demands and offers can be assigned validity periods but also their conditions can be assigned (possibly multiple) validity temporal subintervals. Apart from revising the semantics of procurement tasks, which we previously presented in the first edition of the ICSOC conferences, we also introduce the notion of the covering set of a demand, a topic which is closely related to temporality.
This paper presents a Large Neighborhood Search (LNS) approach based on constraint programming to solve cumulative scheduling problems. It extends earlier work on constraint-based randomized LNS for disjunctive schedu...
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Numerical constraint systems are often handled by branch and prune algorithms that combine splitting techniques, local consistencies, and interval methods. This paper first recalls the principles of Quad, a global con...
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Numerical constraint systems are often handled by branch and prune algorithms that combine splitting techniques, local consistencies, and interval methods. This paper first recalls the principles of Quad, a global constraint that works on a tight and safe linear relaxation of quadratic subsystems of constraints. Then, it introduces a generalization of Quad to polynomial constraint systems. It also introduces a method to get safe linear relaxations and shows how to compute safe bounds of the variables of the linear constraint system. Different linearization techniques are investigated to limit the number of generated constraints. QuadSolver, a new branch and prune algorithm that combines Quad, local consistencies, and interval methods, is introduced. QuadSolver has been evaluated on a variety of benchmarks from kinematics, mechanics, and robotics. On these benchmarks, it outperforms classical interval methods as well as constraint satisfaction problem solvers and it compares well with state-of-the-art optimization solvers.
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