A nurse rostering problem (NRP) deals with the shifts arrangements of nursing staff in the daily operation of a given health care center. This problem is known to be complex mainly due to its combinatorial nature that...
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A nurse rostering problem (NRP) deals with the shifts arrangements of nursing staff in the daily operation of a given health care center. This problem is known to be complex mainly due to its combinatorial nature that commonly requires exponential time to be solved. The literature presents a large list of works devoted to solve NRPs, however most of them are focused on the performance of results of well-known NRP instances, and just a few address real cases. In this paper we present a study of real nurse rostering, which particularly involves a very uncommon shift pattern due to proper country legal regulations. We introduce a new model including soft constraints that can be efficiently solved by employing reified constraints.
For constraint programming (CP), enumeration strategies (selection of a variable and a value of its domain) are crucial for resolution performances. We propose to use Local Search for guiding enumeration: we extend th...
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ISBN:
(纸本)9783901509704
For constraint programming (CP), enumeration strategies (selection of a variable and a value of its domain) are crucial for resolution performances. We propose to use Local Search for guiding enumeration: we extend the common variable selection strategies of CP and we achieve the value selection based on a Local Search. The experimental results are rather promising, both in terms of needed enumerations and in terms of CPU time.
This paper presents a logic language for expressing search and optimization problems. Specifically, first a language obtained by extending (positive) DATALOG with intuitive and efficient constructs (namely, stratifie...
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This paper presents a logic language for expressing search and optimization problems. Specifically, first a language obtained by extending (positive) DATALOG with intuitive and efficient constructs (namely, stratified negation, constraints, and exclusive disjunction) is introduced. Next, a further restricted language only using a restricted form of disjunction to define (nondeterministically) subsets (or partitions) of relations is investigated. This language, called atalog, captures the power of DATALOG¬ in expressing search and optimization problems. A system prototype implementing atalog is presented. The system translates atalog queries into Optimization programming Language (OPL) programs which are executed by the ILOG OPL Development Studio. Our proposal combines easy formulation of problems, expressed by means of a declarative logic language, with the efficiency of the ILOG System. Several experiments show the effectiveness of this approach.
Mixed model assembly lines are used to produce multiple copies of given minimum part set (MPS). Considering only one copy (cycle) of the MPS while solving the mixed-model balancing and scheduling problem yields subopt...
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Mixed model assembly lines are used to produce multiple copies of given minimum part set (MPS). Considering only one copy (cycle) of the MPS while solving the mixed-model balancing and scheduling problem yields suboptimal solutions since blocking and idle times of stations between repeated copies are ignored. Modeling and solving this problem in a cyclic manner can significantly overcome these inefficiencies and improve the throughput of the line. In this paper, after investigating the nature of the problem, we propose exact and heuristic methods for practical applications and evaluate their performances on various size test instances.
An approach to reliable modeling, simulation and verification of hybrid systems is interval arithmetic, which guarantees that a set of intervals narrower than specified size encloses the solution. Interval-based compu...
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An approach to reliable modeling, simulation and verification of hybrid systems is interval arithmetic, which guarantees that a set of intervals narrower than specified size encloses the solution. Interval-based computation of hybrid systems is often difficult, especially when the systems are described by nonlinear ordinary differential equations (ODEs) and nonlinear algebraic equations. We formulate the problem of detecting a discrete change in hybrid systems as a hybrid constraint system (HCS), consisting of a flow constraint on trajectories (i.e. continuous functions over time) and a guard constraint on states causing discrete changes. We also propose a technique for solving HCSs by coordinating (i) interval-based solving of nonlinear ODEs, and (ii) a constraint programming technique for reducing interval enclosures of solutions. The proposed technique reliably solves HCSs with nonlinear constraints. Our technique employs the interval Newton method to accelerate the reduction of interval enclosures, while guaranteeing that the enclosure contains a solution.
A mixed model assembly line is production line where various product models are assembled. Line balancing and model sequencing problems are important for the efficiency of the assembly line. This paper solves them sim...
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A mixed model assembly line is production line where various product models are assembled. Line balancing and model sequencing problems are important for the efficiency of the assembly line. This paper solves them simultaneously aiming to minimize the latest completion time. A mixed integer liner programming model and a constraint programming model are proposed to provide the exact solution of the problem with station‐dependent assembly times. Because of NP‐hardness, a variable neighborhood simulated annealing algorithm is applied and compared to the hybrid simulated annealing algorithm from the literature. To strength the search process, a encoding method and a decoding method were proposed. Numerical results statistically show the efficiency of the proposed algorithm in terms of both the quality of solution and the time of achieving the best solution.
We present in this paper the Model Based System Synthesis (MBSS) approach for the design of complex systems that are correct by construction. Where the usual Model Based System Engineering (MBSE) approach offers forma...
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We present in this paper the Model Based System Synthesis (MBSS) approach for the design of complex systems that are correct by construction. Where the usual Model Based System Engineering (MBSE) approach offers formalisms and tools to represent a candidate system, to analyze it, to simulate it and even to optimize it, MBSS proposes to represent the global design problem using a problem representation language and then to solve it by using adapted synthesis tools producing one or several solutions necessarily satisfying the expressed requirements. The two approaches are therefore complementary; the MBSS being more adapted to the preliminary design and system integration stages. After presenting the different categories of problems encountered in system design (sizing, configuration, allocation, architecture generation), MBSS and MBSE will be positioned in relation to each other. The main concepts of MBSS will be detailed in order to understand the specific representation needs of the approach. The structural and behavioral notions related to the sub-definite systems will be explained as well as the links to be established with the functional and non-functional requirements. The approach is illustrated using the DEPS design problem specification language and the DEPS Studio modeling and solving tool on a system design case study. The DEPS language combines structural modeling features specific to object-oriented principles and ontology definition capabilities for engineers with problem specification features from constraint programming. DEPS Studio is an integrated modeling and solving environment designed to model and resolve system synthesis problems. It allows the engineer to edit, compile, debug and solve problems expressed in DEPS. It integrates a mixed constraint programming solver. The approach can be applied on physical systems, software intensive or mixed systems (embedded or cyber-physical).
The paper introduces the concept of a crystalline-like model of a computer communication network (CCN) composed of routers forming a repeating or periodic arrangement. The considered homogenous network assumes the sam...
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The paper introduces the concept of a crystalline-like model of a computer communication network (CCN) composed of routers forming a repeating or periodic arrangement. The considered homogenous network assumes the same routers servicing the same number of transmissions form an array. In such a network several isomorphic sub-networks encompassing packet transmission processes serviced by each router, interact each other as to provide a variety of demand-responsive host-server transmission services. In that context, a crystalline-like layout of physically different, however functionally identical, routers provides a homogenous array supporting computer network flows. In turn, packet transmission flows are treated as multimodal processes encompassing arbitrarily given inter-computer communications. Assuming the packets passing their origin-destination routes are synchronized by the same mechanism of packet transmission the problem boils down to a communication processes scheduling. Since concurrent transmission flows are processed along the same presumed routes, hence the schedules sought are cyclic ones. In general case, cycles of multimodal processes depend on CNN's periodicity. That objective to develop conditions allowing one to calculate the cyclic schedule of whole CCN while taking into account only periodicity of its repeating isomorphic structure.
Across the world, cardiovascular diseases (CVD) are among the leading causes of death. In Iran, it is estimated that about 46% of all the reported deaths is related to CVD. This article focuses on the patient scheduli...
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Across the world, cardiovascular diseases (CVD) are among the leading causes of death. In Iran, it is estimated that about 46% of all the reported deaths is related to CVD. This article focuses on the patient scheduling practices of a private cardiology clinic in Iran. Several complaints from the patients and staff members of the clinic are reviewed. The study shows that the patients in the clinic are classified into six major groups; the steps each group must undergo in the clinic as well as the time related to each operation is measured. A constraint programming model is developed to schedule the patients and rectify the complaints. Computational results based on 30 days of actual data from the clinic reveals that the proposed model manages to significantly improve the efficiency measures and is successful in resolving the causes of complaints. Furthermore, the developed constraint programming generates optimum solutions in a rather short amount of time.
In this work, the operational production scheduling problem of a manufacturer in the automotive sector, producing injection molded parts, is presented. In order to meet all requirements, including alternative resource...
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In this work, the operational production scheduling problem of a manufacturer in the automotive sector, producing injection molded parts, is presented. In order to meet all requirements, including alternative resources, release dates, due dates and sequence dependent setup times, a schedule classification and a related integer programming formulation for this flexible job-shop scheduling real-world problem is presented. Since the combinatorial complexity of the problem does not allow an efficient optimization for the company partner, a constraint programming approach is proposed, solving the real-world case to optimality within a few seconds of runtime.
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