This paper considers the combination of berth and crane allocation problems in container terminals. We propose a novel approach based on constraint programming which is able to model many realistic operational constra...
详细信息
ISBN:
(纸本)9783642406263;9783642406270
This paper considers the combination of berth and crane allocation problems in container terminals. We propose a novel approach based on constraint programming which is able to model many realistic operational constraints. The costs for berth allocation, crane allocation, time windows, breaks and transition times during gang movements are optimized simultaneously. The model is based on a resource view where gangs are consumed by vessel activities. Side constraints are added independently around this core model. The model is richer than the state of the art in the operations research community. Experiments show that the model produces solutions with a cost gap of 1/10 (7,8%) to 1/5 (18,8%) compared to an ideal operational setting where operational constraints are ignored.
Large neighborhood search (LNS) [25] is a framework that combines the expressiveness of constraint programming with the efficiency of local search to solve combinatorial optimization problems. This paper introduces an...
详细信息
ISBN:
(纸本)9783642406263;9783642406270
Large neighborhood search (LNS) [25] is a framework that combines the expressiveness of constraint programming with the efficiency of local search to solve combinatorial optimization problems. This paper introduces an extension of LNS, called multi-objective LNS (MO-LNS), to solve multi-objective combinatorial optimization problems ubiquitous in practice. The idea of MO-LNS is to maintain a set of nondominated solutions rather than just one best-so-far solution. At each iteration, one of these solutions is selected, relaxed and optimized in order to strictly improve the hypervolume of the maintained set of nondominated solutions. We introduce modeling abstractions into the OscaR solver for MO-LNS and show experimentally the efficiency of this approach on various multi-objective combinatorial optimization problems.
Automata, possibly with counters, allow many constraints to be expressed in a simple and high-level way. An automaton induces a decomposition into a conjunction of already implemented constraints. Generalised arc cons...
详细信息
ISBN:
(纸本)9781479929719
Automata, possibly with counters, allow many constraints to be expressed in a simple and high-level way. An automaton induces a decomposition into a conjunction of already implemented constraints. Generalised arc consistency is not generally maintained on decompositions induced by counter automata with more than one state or counter. To improve propagation of automaton-induced constraint decompositions, we use automated tools to derive loop invariants from the constraint checker corresponding to the given automaton. These loop invariants correspond to implied constraints, which can be added to the decomposition. We consider two global constraints and derive implied constraints to improve propagation even to the point of maintaining generalised arc consistency.
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. This problem con...
详细信息
ISBN:
(纸本)9781467355506;9780769549538
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. This problem consists in computing an optimal planning of communications between satellites or spacecraft (SC) and operations teams of Ground Station (GS). The information transmitted in these communications is usually basic information such as telemetry, tracking or information tasks to be performed and the time normally required for communication is usually quite smaller than the window of visibility of SCs to GSs. The problem is known for its high complexity and has been shown computationally hard to solve to optimality. Additionally, several optimization objectives can be formulated and sought for the problem, namely, windows fitness, clashes fitness, time requirement fitness, and resource usage fitness. In this paper, we present the resolution of the problem through Steady State Genetic Algorithm (SSGA), in which a few individuals are replaced during genetic evolution. We evaluated the performance of the SSGA through a suite of instances generated with the STK simulation toolkit. The Steady State could find for most instances very high quality solutions although its performance was not equally good for all considered objectives.
Secure interoperation is an increasingly important issue for large-scale enterprise applications. In this paper, we investigate, through constraint logic programming (CLP), secure interoperation in collaborating envir...
详细信息
A particularly difficult class of scheduling and routing problems involves an objective that is a sum of time-varying action costs, which increases the size and complexity of the problem. Solve-and-improve approaches,...
详细信息
A range of methodologies and techniques are available to guide the design and implementation of language extensions and domain-specific languages on top of a base language. A simple yet powerful technique to this end ...
详细信息
Recently, researchers in answer set programming and constraint programming spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separat...
详细信息
There is a pressing need in clinical practice to mitigate (identify and address) adverse interactions that occur when a comorbid patient is managed according to multiple concurrently applied disease-specific clinical ...
详细信息
Cumulative resource constraints can model scarce resources in scheduling problems or a dimension in packing and cutting problems. In order to efficiently solve such problems with a constraint programming solver, it is...
详细信息
暂无评论