The electric rail sector, like many sectors, is looking for means to reduce its energy consumption and energy cost. In this work we consider the scenario where the utility provider charges based on the maximum consump...
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ISBN:
(纸本)9781509001637
The electric rail sector, like many sectors, is looking for means to reduce its energy consumption and energy cost. In this work we consider the scenario where the utility provider charges based on the maximum consumption over a period. Therefore one wishes to schedule the departure of trains such that the aggregate load is balanced across time periods while satisfying timetabling and resource restrictions. We present an approach which combines the strengths of a number of research areas such as constraint programming, linear programming, mixed-integer programming, and large neighbourhood search. The empirical performance on instances from an ongoing research challenge demonstrates the approach's ability to dramatically reduce the overall energy cost. In addition, we are able to close a number of the instances for which we prove optimality.
To comply with the continually growing demand for multimedia content and higher throughputs, the telecommunication industry has to keep improving the use of the bandwidth resources, leading to the well-known Frequency...
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As a result of the continually growing demand for multimedia content and higher throughputs in wireless communication systems, the telecommunication industry has to keep improving the use of the bandwidth resources. T...
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Recently, train regulation is being complex because of congested train schedules and various kinds of cars/classes of trains. So it is necessary for decreasing operator's workload and raising his skill to help his...
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The Italian Logic programming community has given several contributions to the theory of Concurrent constraint programming. In particular, in the topics of semantics, verification, and timed extensions. In this paper ...
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In recent years, constraint programming (CP) has been widely applied to solved scheduling problems. As one of the key elements in CP, constraint propagation has been proved to be an efficient methodology to speed up t...
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ISBN:
(纸本)9781424451814;9781424451821
In recent years, constraint programming (CP) has been widely applied to solved scheduling problems. As one of the key elements in CP, constraint propagation has been proved to be an efficient methodology to speed up the search process. In this paper, we develop a hybrid branch and bound algorithm with CP technique, called HCPBAB, which focuses on branches cutting to achieve outstanding performance tuning and constraints handling ability compared with the original method. Moreover, we extend the popular input/output negation, input-or-output constraint propagation process into HCPBAB to extensively test our proposed method. Experimental results on 40 instances taken from standard job shop benchmarks show that 33 instances are optimally solved while HCPBAB obtains 11 better solutions compared with Rego C’s results in 2009.
In recent years,constraint programming(CP) has been widely applied to solved scheduling *** one of the key elements in CP,constraint propagation has been proved to be an efficient methodology to speed up the search **...
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In recent years,constraint programming(CP) has been widely applied to solved scheduling *** one of the key elements in CP,constraint propagation has been proved to be an efficient methodology to speed up the search *** this paper,we develop a hybrid branch and bound algorithm with CP technique,called HCPBAB,which focuses on branches cutting to achieve outstanding performance tuning and constraints handling ability compared with the original ***,we extend the popular input/output negation,input-or-output constraint propagation process into HCPBAB to extensively test our proposed *** results on 40 instances taken from standard job shop benchmarks show that 33 instances are optimally solved while HCPBAB obtains 11 better solutions compared with Rego C's results in 2009.
The authors survey the research and development in Sweden in constraint programming, which is rapidly becoming the method of choice for some kinds of constraint problems, such as scheduling and configuration.
The authors survey the research and development in Sweden in constraint programming, which is rapidly becoming the method of choice for some kinds of constraint problems, such as scheduling and configuration.
This paper presents the concept and realization of configurable resource models as extension of a treatment scheduling system for users in the medical sector. Our approach aims to ease the handling of automated treatm...
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This paper presents the concept and realization of configurable resource models as extension of a treatment scheduling system for users in the medical sector. Our approach aims to ease the handling of automated treatment scheduling by domain experts without the immediate assistance of IT-experts. Configurable resource models were integrated into our automated treatment planning system for medical facilities and support a user-friendly configuration of resources such as specialized treatment rooms, medical devices, or medical staff. In our approach, treatment process models are defined in the BPMN workflow-language by the domain experts. The new concept of configurable resource models allows the end-user to interactively describe the available resources in their environment. These descriptions (i.e. configurable resource objects or CDOs) can then be linked to activities specified in the treatment models. Together, CDOs and the BPMN treatment models are automatically transformed into CSPs, i.e. mathematical descriptions which can be solved by constraint solvers, thus yielding optimal treatment plans.
constraint Satisfaction Problems allow one to expressively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to expressive...
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constraint Satisfaction Problems allow one to expressively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to expressively model set constraint problems and to encode them automatically into SAT instances. Our technique is expressive and less error-prone. We apply it to the Social Golfer Problem and to symmetry breaking of the problem.
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