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33rd Conference and Exposition on Balancing Simulation and Testing (IMAC)

作者： Rauf, Usman Kernicky, Timothy Whelan, Matthew J. Al-Shaer, Ehab Univ N Carolina Dept Software & Informat Syst Charlotte NC 28223 USA Univ N Carolina Dept Civil & Environm Engn 9201 Univ City Blvd Charlotte NC 28223 USA

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.

关键词： Structural identification Finite element model updating constraint programming constraint satisfaction problem Structural health monitoring

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Combining constraint-Based and Imperative programming in MABS for More Reliable Modelling 24th

Combining Constraint-Based and Imperative Programming in MAB...

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24th International Workshop on Multi-Agent-Based Simulation (MABS)

作者： Edmonds, Bruce Polhill, J. Gareth Manchester Metropolitan Univ Ctr Policy Modelling Manchester Lancs England James Hutton Inst Aberdeen Scotland

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.

关键词： constraint programming declarative programming imperative programming Multi-Agent-Based Simulation MABS model joining model comparison internal checks unit tests strong typing

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Multi-Objective Embarrassingly Parallel Search for constraint programming

Multi-Objective Embarrassingly Parallel Search for Constrain...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Yasuhara, M. Miyamoto, T. Mori, K. Kitamura, S. Izui, Y. Osaka Univ Grad Sch Engn Suita Osaka Japan Mitsubishi Electr Corp Adv Technol R&D Ctr Tokyo Japan

ISBN: (纸本)9781467380669

Optimization plays an important role in various disciplines of engineering. Multi-objective optimization is usually characterized by a Pareto front. In large scale multi objective optimization problems, determining an optimal Pareto front consumes large time. Thus, parallel computing is used to speed up the search. constraint programming is one of the logic-based optimization techniques for solving combinatorial optimization problems. Kotecha et al. proposed a constraint programming-based strategy to determine an optimal Pareto front. Regin et al. proposed a parallel search for constraint programming, called the embarrassingly parallel search. In this paper, we propose the multi-objective embarrassingly parallel search for multi-objective constraint optimization, which combines the two strategies.

关键词： multi-objective optimization parallel processing constraint programming Pareto front

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On Complex Hybrid Flexible Flowshop Scheduling Problems Based on constraint programming 12

On Complex Hybrid Flexible Flowshop Scheduling Problems Base...

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12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Zhou, Jinlian Li, Guipeng Guo, Ying Ningxia Inst Sci & Technol Elect & Informat Engn Coll Ningxia Peoples R China Tsinghua Univ Dept Automat TNLIST MOE Key Lab Bioinformat & Bioinformat DivCtr Syn Beijing Peoples R China

ISBN: (纸本)9781467376822

The complex hybrid flexible flowshop problems in the real-world industries scheduling were researched, including constraints of unrelated machines, skipping some stages etc. Though several researches were done to address some of the constraints, modeling these constraints was seldom done simultaneously. This paper modeled the problem in the perspective of constraint programming and solved the problem utilizing the Gecode system. The simulation results showed that our proposed method was efficiently and effectively on solving the complex hybrid flexible flowshop problems. It was the first proposed method to investigate and solve the hybrid flexible flowshop problems using constraint programming.

关键词： Hybrid flexible flowshop scheduling problems constraint programming Gecode Introduction

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Solving Segment Routing Problems with Hybrid constraint programming Techniques 21st

Solving Segment Routing Problems with Hybrid Constraint Prog...

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31st International Conference on Logic programming (ICLP) Co-located with the 21st International Conference on Principles and Practice of constraint programming (CP)

作者： Hartert, Renaud Schaus, Pierre Vissicchio, Stefano Bonaventure, Olivier UCLouvain ICTEAM B-1348 Louvain La Neuve Belgium

ISBN: (纸本)9783319232195;9783319232188

Segment routing is an emerging network technology that exploits the existence of several paths between a source and a destination to spread the traffic in a simple and elegant way. The major commercial network vendors already support segment routing, and several Internet actors are ready to use segment routing in their network. Unfortunately, by changing the way paths are computed, segment routing poses new optimization problems which cannot be addressed with previous research contributions. In this paper, we propose a new hybrid constraint programming framework to solve traffic engineering problems in segment routing. We introduce a new representation of path variables which can be seen as a lightweight relaxation of usual representations. We show how to define and implement fast propagators on these new variables while reducing the memory impact of classical traffic engineering models. The efficiency of our approach is confirmed by experiments on real and artificial networks of big Internet actors.

关键词： Traffic engineering Segment routing constraint programming Large neighborhood search

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Combining Genetic Algorithms and constraint programming to Support Stress Testing of Task Deadlines

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ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2015年第1期25卷 4-4页

作者： Di Alesio, Stefano Briand, Lionel C. Nejati, Shiva Gotlieb, Arnaud Simula Res Lab Software Engn Dept N-1325 Lysaker Norway Univ Luxembourg SnT Ctr L-2721 Luxembourg Luxembourg

Tasks in real-time embedded systems (RTES) are often subject to hard deadlines that constrain how quickly the system must react to external inputs. These inputs and their timing vary in a large domain depending on the environment state and can never be fully predicted prior to system execution. Therefore, approaches for stress testing must be developed to uncover possible deadline misses of tasks for different input arrival times. In this article, we describe stress-test case generation as a search problem over the space of task arrival times. Specifically, we search for worst-case scenarios maximizing deadline misses, where each scenario characterizes a test case. In order to scale our search to large industrial-size problems, we combine two state-of-the-art search strategies, namely, genetic algorithms (GA) and constraint programming (CP). Our experimental results show that, in comparison with GA and CP in isolation, GA+CP achieves nearly the same effectiveness as CP and the same efficiency and solution diversity as GA, thus combining the advantages of the two strategies. In light of these results, we conclude that a combined GA+CP approach to stress testing is more likely to scale to large and complex systems.

关键词： Experimentation Measurement Performance Reliability Real-time systems stress testing task deadline search-based software testing genetic algorithms constraint programming

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constraint programming and Ant Colony System for the Component Deployment Problem

Constraint Programming and Ant Colony System for the Compone...

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14th Annual International Conference on Computational Science

作者： Thiruvady, Dhananjay Moser, I. Aleti, Aldeida Nazari, Asef CSIRO Computat Informat Clayton Vic 3169 Australia Swinburne Univ Technol Fac Sci Engn & Technol Melbourne Vic Australia Monash Univ Clayton Sch IT Clayton Vic 3800 Australia

Contemporary motor vehicles have increasing numbers of automated functions to augment the safety and comfort of a car. The automotive industry has to incorporate increasing numbers of processing units in the structure of cars to run the software that provides these functionalities. The software components often need access to sensors or mechanical devices which they are designed to operate. The result is a network of hardware units which can accommodate a limited number of software programs, each of which has to be assigned to a hardware unit. A prime goal of this deployment problem is to find software-to-hardware assignments that maximise the reliability of the system. In doing so, the assignments have to observe a number of constraints to be viable. This includes limited memory of a hardware unit, collocation of software components on the same hardware units, and communication between software components. Since the problem consists of many constraints with a significantly large search space, we investigate an ACO and constraint programming (CP) hybrid for this problem. We find that despite the large number of constraints, ACO on its own is the most effective method providing good solutions by also exploring infeasible regions.

关键词： Component Deployment Problem constraint programming Ant Colony System Combinatorial Optimisation

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constraint programming method for Crew Schedule Recovery

Constraint programming method for Crew Schedule Recovery

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4th International Conference on Frontiers of Manufacturing and Design Science (ICFMD 2013)

作者： Zhu, Bo Cao, Xiangling Wang, Yu Gao, Qiang Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing 211106 Jiangsu Peoples R China Civil Aviat Flight Univ China Sch Air Transportat Management Guanghan 618307 Peoples R China

ISBN: (纸本)9783037859926

Unexpected disruptions such as aircraft failure and airport closure often make the original flight schedule cannot operate regularly and destroy the crew duties. This paper proposed a constraint programming model to solve the crew recovery problem. The total recovery cost was taken as the objective function, temporal-spacial requirements, deadheading and time legalities were considered as constraints. An algorithm based on sequential, least slack and greedy thoughts was designed to search the solution space. Finally, an example was test to indicated feasibility of the proposed model and algorithm.

关键词： air transportation crew recovery constraint programming search strategy

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constraint programming Solving in Fuzzy Models

Constraint Programming Solving in Fuzzy Models

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23rd International-Business-Information-Management-Association Conference on Visio 2020: Sustainable Growth, Economic Development, and Global Competitiveness

作者： Tudor, Liviana N. Petr Gas Univ Ploiesti Dept Informat Technol Ploiesti Romania

ISBN: (纸本)9780986041921

This paper presents a fuzzy reasoning pattern using some logic programming techniques. A fuzzy approach of a multi-attribute decisional problem is developed. The proposed system offers a model of constraint programming solving for finite domain. A case study is achieved for choosing the optimal merging variant of two companies from more similar suggestions.

关键词： inductive logic programming constraint programming multi-attribute decisional problem fuzzy reasoning

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Machine-Part Cell Formation Problems with constraint programming

Machine-Part Cell Formation Problems with Constraint Program...

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International Conference of the Chilean Computer Science Society

作者： Ricardo Soto Broderick Crawford Boris Almonacid Fernando Paredesll Ernesto Loyola Pontificia Universidad Católica de Valparaiso Valparaiso Chile Escuela de Ingeniería Industrial Universidad Diego Portales Chile Universidad Católica del Norte Chile

ISBN: (纸本)9781467398183

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.

关键词： Machine-Part Cell Formation constraint programming Optimization

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