The pattern minimization problem is a cutting and packing problem that consists in finding a cutting plan with the minimum number of different patterns. This objective may be relevant when changing from one pattern to...
详细信息
The pattern minimization problem is a cutting and packing problem that consists in finding a cutting plan with the minimum number of different patterns. This objective may be relevant when changing from one pattern to another involves a cost for setting up the cutting machine. When the minimization of the number of different patterns is done by assuming that no more than the minimum number of rolls can be used, the problem is also referred to as the cutting stock problem with setup costs. Most of the approaches described in the literature are based on heuristics. Solving the problem exactly has been a real challenge, and only very few exact solution methods have been reported so far in the literature. In this paper, we intend to contribute to the resolution of the pattern minimization problem with new results. We explore a different integer programming model that can be solved using column generation, and we describe different strategies to strengthen it, among which are constraint programming and new families of valid inequalities. Lower bounds for the pattern minimization problem are derived from the new integer programming model, and also from a constraint programming model. Our approaches were tested on a set of real instances, and on a set of random instances from the literature. For these instances, the computational experiments show a clear improvement on the quality of the lower bounds. (C) 2009 Elsevier Ltd. All rights reserved.
Within the area of short term airline operational planning, Tail Assignment is the problem of assigning flight legs to individual identified aircraft while satisfying all operational constraints, and optimizing some o...
详细信息
Within the area of short term airline operational planning, Tail Assignment is the problem of assigning flight legs to individual identified aircraft while satisfying all operational constraints, and optimizing some objective function. In this article, we propose that Tail Assignment should be solved as part of both the short and the long term airline planning. We further present a hybrid column generation and constraint programming solution approach. This approach can be used to quickly produce solutions for operations management, and also to produce close-to-optimal solutions for long and mid term planning scenarios. We present computational results which illustrate the practical usefulness of the approach.
We propose a new two-level decomposition algorithm for shift scheduling problems. The problem determines the assignment of duties and rest days to the set of staff members to minimize the given objective function. The...
详细信息
ISBN:
(纸本)9781479938407
We propose a new two-level decomposition algorithm for shift scheduling problems. The problem determines the assignment of duties and rest days to the set of staff members to minimize the given objective function. The constraint on the set of staff members are considered. The objective of this paper is to achieve the minimization of total costs with fairness of working conditions. The proposed method decomposes the original problem into the master and the subproblems. These subproblems are iteratively solved with embedding cuts into the master problem. Computational results show that the performance of the proposed method outperforms a general-purpose constraint logic programming solver.
Considerable effort has been invested over the years in ad-hoc algorithms for itemset and pattern mining. constraint programming has recently been proposed as a means to tackle itemset mining tasks within a general mo...
详细信息
ISBN:
(纸本)9781479965731
Considerable effort has been invested over the years in ad-hoc algorithms for itemset and pattern mining. constraint programming has recently been proposed as a means to tackle itemset mining tasks within a general modelling framework. We follow this approach to address the discovery of discriminative n-ary motifs in databases of labeled sequences. We define a n-ary motif as a mapping of n patterns to n class-wide embeddings and we restrict the interpretation of constraints on a motif to the sequences embedding all patterns. We formulate core constraints that minimize redundancy between motifs and introduce a general constraint optimization framework to compute common and exclusive motifs. We cast the discovery of closed and replication-free motifs in this framework for which we propose a two-stage approach based on constraint programming. Experimental results on datasets of protein sequences demonstrate the efficiency of the approach.
Real-life management decisions are usually made in uncertain environments, and decision support systems that ignore this uncertainty are unlikely to provide realistic guidance. We show that previous approaches fail to...
详细信息
Real-life management decisions are usually made in uncertain environments, and decision support systems that ignore this uncertainty are unlikely to provide realistic guidance. We show that previous approaches fail to provide appropriate support for reasoning about reliability under uncertainty. We propose a new framework that addresses this issue by allowing logical dependencies between constraints. Reliability is then defined in terms of key constraints called "events", which are related to other constraints via these dependencies. We illustrate our approach on three problems, contrast it with existing frameworks, and discuss future developments.
Directed Acyclic Task Graphs serve as typical kernel representation for embedded applications. Modern embedded multicore architectures raise new challenges for efficient mapping and scheduling of task DAGs providing a...
详细信息
ISBN:
(纸本)9781479941162
Directed Acyclic Task Graphs serve as typical kernel representation for embedded applications. Modern embedded multicore architectures raise new challenges for efficient mapping and scheduling of task DAGs providing a large number of heterogeneous resources. In this paper, a hybrid Integer Linear programming - constraint programming method that uses the Benders decomposition is used to find proven optimal solutions. The proposed method is augmented with cuts generation schemes for accelerating the solution process. Experimental results show that the proposed method systematically outperforms an ILP-based solution method.
Component-based Software Engineering (CBSE) is currently a key paradigm used for developing safetycritical systems. It provides a fundamental means to master systems complexity, by allowing to design systems parts (i....
详细信息
Component-based Software Engineering (CBSE) is currently a key paradigm used for developing safetycritical systems. It provides a fundamental means to master systems complexity, by allowing to design systems parts (i. e., components) for reuse and by allowing to develop those parts independently. One of the main challenges of introducing CBSE in this area is to ensure the integrity of the overall system after building it from individual components, since safety-critical systems require a rigorous development and qualification process to be released for the operation. Although the topic of compositional modelling and verification in the context of component-based systems has been studied intensively in the last decade, there is currently still a lack of tools and methods that can be applied practically and that consider major related systems quality attributes such as usability and scalability. In this paper, we present a novel approach for design-time modelling and verification of safety-critical systems, based on data semantics of components. We describe the composition, i. e., the systems design, and the underlying properties of components as a constraint Satisfaction Problem (CSP) and perform the verification by solving that problem. We show that CSP can be successfully applied for the verification of compositions for many types of properties. In our experimental setup we also show how the proposed verification scales with regard to the complexity of different system configurations.
This paper introduces a new constraint domain for reasoning about data with uncertainty. It extends convex modeling with the notion of p-box to gain additional quantifiable information on the data whereabouts. Unlike ...
详细信息
This paper introduces a new constraint domain for reasoning about data with uncertainty. It extends convex modeling with the notion of p-box to gain additional quantifiable information on the data whereabouts. Unlike existing approaches, the p-box envelops an unknown probability instead of approximating its representation. The p-box bounds are uniform cumulative distribution functions (cdf)in order to employ linear computations in the probabilistic domain. The reasoning by means of p-box cdf-intervals is an interval computation which is exerted on the real domain then it is projected onto the cdf domain. This operation conveys additional knowledge represented by the obtained probabilistic bounds. The empirical evaluation of our implementation shows that, with minimal overhead, the output solution set realizes a full enclosure of the data along with tighter bounds on its probabilistic distributions.
Linear integer constraints are one of the most important constraints in combinatorial problems since they are commonly found in many practical applications. Typically, encoding linear constraints to SAT performs poorl...
详细信息
ISBN:
(纸本)9783319104287;9783319104270
Linear integer constraints are one of the most important constraints in combinatorial problems since they are commonly found in many practical applications. Typically, encoding linear constraints to SAT performs poorly in problems with these constraints in comparison to constraint programming (CP) or mixed integer programming (MIP) solvers. But some problems contain a mix of combinatoric constraints and linear constraints, where encoding to SAT is highly effective. In this paper we define new approaches to encoding linear constraints into SAT, by extending encoding methods for pseudo-Boolean constraints. Experimental results show that these methods are not only better than the state-of-the-art SAT encodings, but also improve on MIP and CP solvers on appropriate problems. Combining the new encoding with lazy decomposition, which during runtime only encodes constraints that are important to the solving process that occurs, gives a robust approach to many highly combinatorial problems involving linear constraints.
The navigation constellation will have the capability of supporting Tracking Telemetry and Command (TT&C) operations by inter-satellite link (ISL). The ISL will become an important solution to reduce the shortage ...
详细信息
ISBN:
(纸本)9781629939094
The navigation constellation will have the capability of supporting Tracking Telemetry and Command (TT&C) operations by inter-satellite link (ISL). The ISL will become an important solution to reduce the shortage of ground TT&C resources. The problems need to be studied urgently in the field of space TT&C network resources scheduling management are how to determine the availability of ISL and how to allocate TT&C resources of ISL. The performance and scheduling constraints of navigation constellation's ISL are analyzed, and three utilization strategies of ISL to perform TT&C operations are proposed. The allocation of TT&C resources based on ISL falls into two successive phases. Firstly, master satellite determination equation is established by using 0-1 programming model based on the availability matrix. Mathematical method is used to solve the equation to determine the master satellite and the topology of ISL. Secondly, constraint programming (CP) model is used to describe the ground TT&C resources scheduling problem with special requirements of TT&C operations based on master satellite, and a heuristic algorithm is designed to solve the CP model. The equations and algorithm are verified by simulation examples. The algorithm of TT&C resources scheduling based on ISL has realized the synthesized usage of both the ISL and ground resources on TT&C field. This algorithm can improve TT&C supports of territorial ground TT&C network for global navigation constellation, and provides technical reference for the TT&C mission planning of global constellation by using ISL. (C) 2014 IAA. Published by Elsevier Ltd. All rights reserved.
暂无评论