Service requesters with limited technical knowledge should be able to compare services based on their quality of service (QoS) requirements in cloud service marketplaces. Existing service matching approaches focus on ...
详细信息
ISBN:
(纸本)9781467376921
Service requesters with limited technical knowledge should be able to compare services based on their quality of service (QoS) requirements in cloud service marketplaces. Existing service matching approaches focus on QoS requirements as discrete numeric values and intervals. The analysis of existing research on non-functional properties reveals two improvement opportunities: list-typed QoS properties as well as explicit handling of preferences for lower or higher property values. We develop a concept and constraint models for a service matcher which contributes to existing approaches by addressing these issues using constraint solvers. The prototype uses an API at the standardisation stage and discovers implementation challenges. This paper concludes that constraint solvers provide a valuable tool to solve the service matching problem with soft constraints and are capable of covering all QoS property types in our analysis. Our approach is to be further investigated in the application context of cloud federations.
This paper presents a constraint programming (CP) methodology to deal with the scheduling of flexible manufacturing systems (FMSs). The proposed approach, which consists of both a model and a search strategy, handles ...
详细信息
This paper presents a constraint programming (CP) methodology to deal with the scheduling of flexible manufacturing systems (FMSs). The proposed approach, which consists of both a model and a search strategy, handles several features found in industrial environments, such as limitations on number of tools in the system, lifetime of tools, as well as tool magazine capacity of machines. In addition, it tackles the problem in a integrated way by considering tool planning and allocation, machine assignment, part routing, and task timing decisions altogether in the approach. The formulation, which is able to take into account a variety of objective functions, has been successfully applied to the solution of test problems of various sizes and degrees of difficulty. (C) 2010 Elsevier Ltd. All rights reserved.
constraint programming can be divided very crudely into modeling and solving. Modeling defines the problem, in terms of variables that can take on different values, subject to restrictions (constraints) on which combi...
详细信息
ISBN:
(纸本)9781577354635
constraint programming can be divided very crudely into modeling and solving. Modeling defines the problem, in terms of variables that can take on different values, subject to restrictions (constraints) on which combinations of variables are allowed. Solving finds values for all the variables that simultaneously satisfy all the constraints. However, the impact of constraint programming has been constrained by a lack of "user-friendliness". constraint programming has a major "declarative" aspect, in that a problem model can be handed off for solution to a variety of standard solving methods. These methods are embedded in algorithms, libraries, or specialized constraint programming languages. To fully exploit this declarative opportunity however, we must provide more assistance and automation in the modeling process, as well as in the design of application-specific problem solvers. Automated modelling and solving in constraint programming presents a major challenge for the artificial intelligence community. Artificial intelligence, and in particular machine learning, is a natural field in which to explore opportunities for moving more of the burden of constraint programming from the user to the machine. This paper presents technical challenges in the areas of constraint model acquisition, formulation and reformulation, synthesis of filtering algorithms for global constraints, and automated solving. We also present the metrics by which success and progress can be measured.
The traditional approach to Model Expansion (MX) is to reduce the theory to a propositional language and apply a search algorithm to the resulting theory. Function symbols are typically replaced by predicate symbols r...
详细信息
ISBN:
(纸本)9781479929719
The traditional approach to Model Expansion (MX) is to reduce the theory to a propositional language and apply a search algorithm to the resulting theory. Function symbols are typically replaced by predicate symbols representing the graph of the function, an operation that blows up the reduced theory. In this paper, we present an improved approach to handle function symbols in a ground-and-solve methodology, building on ideas from constraint programming. We do so in the context of FO(.)(IDP), the knowledge representation language that extends First-Order Logic (FO) with, among others, inductive definitions, arithmetic and aggregates. An MX algorithm is developed, consisting of (i) a grounding algorithm for FO(.)(IDP), parametrised by the function symbols allowed to occur in the reduced theory, and (ii) a search algorithm for unrestricted, ground FO(.)(IDP). The ideas are implemented in the IDP knowledge-base system and experimental evaluation shows that both more compact groundings and improved search performance are obtained.
Indoor location is a growing topic for hospitals, retirement homes and in case of emergency. For the resource efficient (indoor) positioning of mobile individuals an optimized distribution of the used sensors is neces...
详细信息
ISBN:
(纸本)9798350310085
Indoor location is a growing topic for hospitals, retirement homes and in case of emergency. For the resource efficient (indoor) positioning of mobile individuals an optimized distribution of the used sensors is necessary. The placement of beacons (sensors) in a building (indoor positioning) can be a difficult and laborious task, especially if done by hand. Multiple researchers already tried to tackle this problem using different algorithms and under the consideration of distinct use cases. However, none of the currently known methods incorporate constraint programming by using only Boolean variables. In this paper we tried to develop a new method for an efficient placement of Bluetooth Low Energy (BLE) beacons in an indoor scenario. More specifically, we try to optimize the beacons for a trilateration algorithm used for indoor positioning. This algorithm requires that three beacons should be in range for every possible position in the building. In a next step the initially calculated beacon positions are further optimized. This is done by trying to reduce the number of beacons used. Afterwards we evaluate the quality of the beacon placements by comparing it against a manually optimized beacon placement and evaluating it in an existing building by checking the quality of multiple sample positions.
We study the application of constraint programming (CP) to the planning and scheduling of multiple social robots interacting with residents in a retirement home. The robots autonomously organize and facilitate group a...
详细信息
ISBN:
(纸本)9783319449531;9783319449524
We study the application of constraint programming (CP) to the planning and scheduling of multiple social robots interacting with residents in a retirement home. The robots autonomously organize and facilitate group and individual activities among residents. The application is a multi-robot task allocation and scheduling problem in which task plans must be determined that integrate with resident schedules. The problem involves reasoning about disjoint time windows, inter-schedule task dependencies, user and robot travel times, as well as robot energy levels. We propose mixed-integer programming (MIP) and CP approaches for this problem and investigate methods for improving our initial CP approach using symmetry breaking, variable ordering heuristics, and large neighbourhood search. We introduce a relaxed CP model for determining provable bounds on solution quality. Experiments indicate substantial superiority of the initial CP approach over MIP, and subsequent significant improvements in the CP approach through our manipulations. This work is one of the few, of which we are aware, that applies CP to multi-robot task allocation and scheduling problems. Our results demonstrate the promise of CP scheduling technology as a general optimization infrastructure for such problems.
The dismantling and recycling of aircrafts is one of the future challenges for the air transport industry in terms of sustainability. This problem is hard to solve and optimize as planning operations are highly constr...
详细信息
ISBN:
(数字)9783031605994
ISBN:
(纸本)9783031606014;9783031605994
The dismantling and recycling of aircrafts is one of the future challenges for the air transport industry in terms of sustainability. This problem is hard to solve and optimize as planning operations are highly constrained. Indeed, extracting each part requires technicians with the necessary qualifications and equipment. The parts to be extracted are constrained by precedence relations and the number of simultaneous technicians on specific zones is restricted. It is also essential to avoid unbalancing the aircraft during disassembly. Cost is a significant factor, influenced by the duration of ground mobilization and the choice of technicians for each operation. This paper presents a first constraint programming model for this problem using optional interval variables. This model is used to solve variations of a large instance involving up to 1500 tasks, based on real-life data provided by our industrial partner. The results show that the model can find feasible solutions for all variations of the instance and compares the solutions obtained to lower bounds.
We use a local search method we term Large Neighbourhood Search (LNS) to solve vehicle routing problems. LNS is analogous to the shuffling technique of job-shop scheduling, and so meshes well with constraint programmi...
详细信息
ISBN:
(纸本)3540652248
We use a local search method we term Large Neighbourhood Search (LNS) to solve vehicle routing problems. LNS is analogous to the shuffling technique of job-shop scheduling, and so meshes well with constraint programming technology. LNS explores a large neighbourhood of the current solution by selecting a number of "related" customer visits to remove from the set of planned routes. and re-inserting these visits using a constraint-based tree search. Unlike similar methods, we use Limited Discrepancy Search during the tree search to re-insert visits. We analyse the performance of our method on benchmark problems. We demonstrate that results produced are competitive with Operations Research meta-heuristic methods. indicating that constraint-based technology is directly applicable to vehicle routing problems.
A container vessel carries containers of various characteristics, in terms of size, weight, and contents. The cargo load of a container vessel, being subjected to a set of operational conditions and restrictions regar...
详细信息
A container vessel carries containers of various characteristics, in terms of size, weight, and contents. The cargo load of a container vessel, being subjected to a set of operational conditions and restrictions regarding ship stability and safety, is a fundamental element in decision-making when a shipping line provides logistics services to clients. This study presents a constraint programming-based model for the capacity planning of a container vessel under various operational conditions. The proposed model generates base solutions and is complemented with a rich scenario-based analysis that utilizes real-life ship data of a container vessel operated by a liner shipping company with a significant market presence. Solutions obtained from the model provide insights on containership capacity planning with differing settings and search strategies. Recommendations to container carriers, regarding improved capacity planning, are the highlights of the study.
In this paper, we propose a constraint programming model for the design problem of cellular wireless communication networks. It consists of selecting the location of the base station controllers (BSCs) and mobile serv...
详细信息
ISBN:
(纸本)0780377818
In this paper, we propose a constraint programming model for the design problem of cellular wireless communication networks. It consists of selecting the location of the base station controllers (BSCs) and mobile service switching centres (MSCs), selecting their types, designing the network topology and selecting the link types, and considering the location of base transceiver stations (BTSs). Next, we propose a heuristic to find a good solution of the model in a reasonable amount of time. This heuristic is a local search combined with constraint programming techniques. Numerical results show that our approach, on average, found better solutions than the best algorithm of the literature.
暂无评论