In this study we consider the mapping of the main characteristics, i.e., the structural properties, of a classical job shop problem onto well-known combinatorial techniques, i.e., positional sets, disjunctive graphs, ...
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In this study we consider the mapping of the main characteristics, i.e., the structural properties, of a classical job shop problem onto well-known combinatorial techniques, i.e., positional sets, disjunctive graphs, and linear orderings. We procedurally formulate three different models in terms of mixed integer programming (MIP) and constraint programming (CP) paradigms. We utilize the properties of positional sets and disjunctive graphs to construct tight MIP formulations in an efficient manner. In addition, the properties are retrieved by the polyhedral structures of the linear ordering and they are defined on a disjunctive graph to facilitate the formulation of the CP model and to reduce the number of dominant variables. The proposed models are solved and their computational performance levels are compared with well-known benchmarks in the job shop research area using IBM ILog Cplex software. We provide a more explicit analogy of the applicability of the proposed models based on parameters such as time efficiency, thereby producing strong bounds, as well as the expressive power of the modeling process. We also discuss the results to determine the best formulation, which is computationally efficient and structurally parsimonious with respect to different criteria. (C) 2014 Elsevier Inc. All rights reserved.
NoC technology is composed of packet-based interconnections, where the communication resources are distributed across the network. Therefore, the optimal resource utilization is a crucial consideration for efficient a...
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NoC technology is composed of packet-based interconnections, where the communication resources are distributed across the network. Therefore, the optimal resource utilization is a crucial consideration for efficient architectural designs. This paper studies the practicality of the constraint programming (CP) models for NoC architecture designs that effectively use a regular mesh with wormhole switching and the XY routing. The complexity of the CP models is compared with the earlier Mixed Integer programming (MIP) models. Practical CP-based mapping and scheduling models are developed and results are reported on the benchmark datasets. Results indicate that mapping and scheduling problems can be solved at near optimality even under relatively shorter run-time limits as compared to those required by the MIP models.
Elastic optical network (EON) is a novel optical technology introduced recently to provide flexible and multibitrate data transmission in the optical layer. Since many new network services including cloud computing an...
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Elastic optical network (EON) is a novel optical technology introduced recently to provide flexible and multibitrate data transmission in the optical layer. Since many new network services including cloud computing and content delivery networks are provisioned with the use of specialized data centers located in different network nodes, in place of one-to-one unicast transmission, the anycast transmission defined as one-toone-of-many gains much popularity as a quite simple way to improve network performance. Therefore, this article focuses on modeling and static optimization of anycast flows in EONs. In particular, a NP-hard Routing and Spectrum Allocation for Restoration of Anycast Flows (RSA/RAF) problem is formulated. Next, various optimization approaches are proposed to solve this problem, namely, integer linear programming (ILP) using branch and bound algorithm, constraint programming (CP), and various heuristic approaches. Extensive numerical experiments are run to evaluate and compare all proposed methods. The main conclusion is that in some cases the CP approach is more efficient than the ILP modeling. Moreover, the results show that the SA algorithm significantly outperforms other heuristic methods. (c) 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(4), 253-266 2015
Context: Testing complex industrial robots (CIRs) requires testing several interacting control systems. This is challenging, especially for robots performing process-intensive tasks such as painting or gluing, since t...
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Context: Testing complex industrial robots (CIRs) requires testing several interacting control systems. This is challenging, especially for robots performing process-intensive tasks such as painting or gluing, since their dedicated process control systems can be loosely coupled with the robot's motion control. Objective: Current practices for validating CIRs involve manual test case design and execution. To reduce testing costs and improve quality assurance, a trend is to automate the generation of test cases. Our work aims to define a cost-effective automated testing technique to validate CIR control systems in an industrial context. Method: This paper reports on a methodology, developed at ABB Robotics in collaboration with SIMULA, for the fully automated testing of CIRs control systems. Our approach draws on continuous integration principles and well-established constraint-based testing techniques. It is based on a novel constraint-based model for automatically generating test sequences where test sequences are both generated and executed as part of a continuous integration process. Results: By performing a detailed analysis of experimental results over a simplified version of our constraint model, we determine the most appropriate parameterization of the operational version of the constraint model. This version is now being deployed at ABB Robotics's CIR testing facilities and used on a permanent basis. This paper presents the empirical results obtained when automatically generating test sequences for CIRs at ABB Robotics. In a real industrial setting, the results show that our methodology is not only able to detect reintroduced known faults, but also to spot completely new faults. Conclusion: Our empirical evaluation shows that constraint-based testing is appropriate for automatically generating test sequences for CIRs and can be faithfully deployed in an industrial context. (C) 2014 Elsevier B.V. All rights reserved.
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 ...
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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.
Machine-Part Cell Formation consists on organizing a plant as a set of cells, each one of them processing machines containing different part types. In recent years, different techniques have been used to solve this pr...
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ISBN:
(纸本)9781467398176
Machine-Part Cell Formation consists on organizing a plant as a set of cells, each one of them processing machines containing different part types. In recent years, different techniques have been used to solve this problem ranging from exact to approximate methods. This paper focuses on solving new instances of this problem for which no optimal value exists by using the classic Boctor's mathematical model. We employ constraint programming as the underlying solving technique illustrating that global optimums are achieved for the whole set of tested instances.
given a simple graph G = (V, E), the problem dealt with in this paper ask to transform a graph G by, only removing a minimum number of edges, into a disjoint union of cliques. This optimization problem is known to be ...
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ISBN:
(纸本)9781614995890;9781614995883
given a simple graph G = (V, E), the problem dealt with in this paper ask to transform a graph G by, only removing a minimum number of edges, into a disjoint union of cliques. This optimization problem is known to be NP-hard and is referred to as the Cluster Deletion problem (CD). This observation has motivated us to improve the chance for finding a disjoint union of cliques in a limited amount of search. To this end, we propose an encoding of CD in terms of a Weighted constraint Satisfaction Problem (WCSP), a framework which has been widely used in solving hard combinatorial problems. We compare our approach with a fixed-parameter tractability FPT algorithm, which is one of the most used algorithm for solving the Cluster Deletion problem. Then, we experimentally show that the best results are obtained using the new encoding. We report a comparison of the quality and running times of WCSP and FPT algorithms on both random graphs and protein similarity graphs derived from the COG dataset.
The goal of constraint-based sequence mining is to find sequences of symbols that are included in a large number of input sequences and that satisfy some constraints specified by the user. Many constraints have been p...
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ISBN:
(纸本)9783319180083;9783319180076
The goal of constraint-based sequence mining is to find sequences of symbols that are included in a large number of input sequences and that satisfy some constraints specified by the user. Many constraints have been proposed in the literature, but a general framework is still missing. We investigate the use of constraint programming as general framework for this task. We first identify four categories of constraints that are applicable to sequence mining. We then propose two constraint programming formulations. The first formulation introduces a new global constraint called exists-embedding. This formulation is the most efficient but does not support one type of constraint. To support such constraints, we develop a second formulation that is more general but incurs more overhead. Both formulations can use the projected database technique used in specialised algorithms. Experiments demonstrate the flexibility towards constraint-based settings and compare the approach to existing methods.
Structural identification of civil infrastructures, using measured modal properties, remains a promising research field with many applications in performance-based civil engineering and structural health monitoring. I...
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ISBN:
(纸本)9783319152486;9783319152479
Structural identification of civil infrastructures, using measured modal properties, remains a promising research field with many applications in performance-based civil engineering and structural health monitoring. In particular, either computationally swift or direct methods for identifying structural models from partially described and incomplete modal parameter estimates are of foremost interest to facilitate near real-time and reliable structural performance assessment and diagnostics. This paper proposes modeling structural systems as constraint Satisfaction Problems (CSPs) for structural identification to solve for uncertain parameters in structural models. Consistent with measurement data, modal parameter estimates are treated as truncated both in terms of the number of modes measured and the number of measured degrees of freedom relative to the analytical model, which yields a challenging nonlinear inverse eigenvalue problem. Using nonlinear constraints and parameter bounds, the constraint programming approach is demonstrated to be capable of properly reconstructing estimates of both uncertain structural parameters and unmeasured modal parameters for a truss model with only a limited number of measured degrees of freedom.
We argue for a combination of declarative/constraint and imperative programming approaches for MABS: a declarative layer that specified the ontology, assumptions, types, internal and checks for a simulation and the im...
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ISBN:
(纸本)9783031610332;9783031610349
We argue for a combination of declarative/constraint and imperative programming approaches for MABS: a declarative layer that specified the ontology, assumptions, types, internal and checks for a simulation and the imperative code that satisfied the statements of the declarative layer - instantiating the behaviours. Such a system would be a generalisation of common elements of existing simulations. The two layers would be separately developed and communicated but work together. Using such a system one might: (a) start by importing an ontology of entities that have been previously agreed within a field, (b) work with domain experts to implement declarative statements that reflect what is known about the system, (c) develop the implementation starting with declarative internal checks and the outlines of the implementation, (d) slowly add imperative statements to fill in details, (e) finally when the simulation has been completely verified, the declarative layer could be switched off to allow faster exploration. This would ensure for a more reliable simulation and ensure its consistency with common ontologies etc. It would facilitate: joining models together with fewer mistakes, comparing models, provide enhanced and flexible error checking, make modules more reusable, allow for rapid prototyping, support the automation of modelling tools/add-ons, and allow the selective exploration of all possible behaviours of a sub-model using constraint programming techniques. Examples are given of previous work that moves in this direction.
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