979 resultados para Constraint Satisfaction Problem
Resumo:
This research paper has been written with the intention to discuss the problem of discipline in Cape Verdean secondary schools. While many of us discuss the effects that student misbehavior has on the student misbehavior has on the student, school and society as a whole, very few of us seek solutions which would impact on the prevention and management of this problem that each day becomes more complicated and harder to handle. This paper will discuss the need to better define discipline at the school level; identify the causes and factors that aggravate the problem, in addition, to provide what I hope to be useful strategies to better manage the problem as we make the effort to reclaim our schools and better educate our students. My research included surveys completed by teachers and student alike as they baffled over the question: what is discipline and how can we better manage discipline problems at our schools?
Resumo:
The standard one-machine scheduling problem consists in schedulinga set of jobs in one machine which can handle only one job at atime, minimizing the maximum lateness. Each job is available forprocessing at its release date, requires a known processing timeand after finishing the processing, it is delivery after a certaintime. There also can exists precedence constraints between pairsof jobs, requiring that the first jobs must be completed beforethe second job can start. An extension of this problem consistsin assigning a time interval between the processing of the jobsassociated with the precedence constrains, known by finish-starttime-lags. In presence of this constraints, the problem is NP-hardeven if preemption is allowed. In this work, we consider a specialcase of the one-machine preemption scheduling problem with time-lags, where the time-lags have a chain form, and propose apolynomial algorithm to solve it. The algorithm consist in apolynomial number of calls of the preemption version of the LongestTail Heuristic. One of the applicability of the method is to obtainlower bounds for NP-hard one-machine and job-shop schedulingproblems. We present some computational results of thisapplication, followed by some conclusions.
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We start with a generalization of the well-known three-door problem:the n-door problem. The solution of this new problem leads us toa beautiful representation system for real numbers in (0,1] as alternated series, known in the literature as Pierce expansions. A closer look to Pierce expansions will take us to some metrical properties of sets defined through the Pierce expansions of its elements. Finally, these metrical properties will enable us to present 'strange' sets, similar to the classical Cantor set.
Resumo:
One of the assumptions of the Capacitated Facility Location Problem (CFLP) is thatdemand is known and fixed. Most often, this is not the case when managers take somestrategic decisions such as locating facilities and assigning demand points to thosefacilities. In this paper we consider demand as stochastic and we model each of thefacilities as an independent queue. Stochastic models of manufacturing systems anddeterministic location models are put together in order to obtain a formula for thebacklogging probability at a potential facility location.Several solution techniques have been proposed to solve the CFLP. One of the mostrecently proposed heuristics, a Reactive Greedy Adaptive Search Procedure, isimplemented in order to solve the model formulated. We present some computationalexperiments in order to evaluate the heuristics performance and to illustrate the use ofthis new formulation for the CFLP. The paper finishes with a simple simulationexercise.
Resumo:
The problems arising in commercial distribution are complex and involve several players and decision levels. One important decision is relatedwith the design of the routes to distribute the products, in an efficient and inexpensive way.This article deals with a complex vehicle routing problem that can beseen as a new extension of the basic vehicle routing problem. The proposed model is a multi-objective combinatorial optimization problemthat considers three objectives and multiple periods, which models in a closer way the real distribution problems. The first objective is costminimization, the second is balancing work levels and the third is amarketing objective. An application of the model on a small example, with5 clients and 3 days, is presented. The results of the model show the complexity of solving multi-objective combinatorial optimization problems and the contradiction between the several distribution management objective.
Resumo:
The general objective of the study was to empirically test a reciprocal model of job satisfaction and life satisfaction while controlling for some social demographic variables. 827 employees working in 34 car dealerships in Northern Quebec (56% responses rate) were surveyed. The multiple item questionnaires were analysed using correlation analysis, chi square and ANOVAs. Results show interesting patterns emerging for the relationships between job and life satisfaction of which 49.2% of all individuals have spillover, 43.5% compensation, and 7.3% segmentation type of relationships. Results, nonetheless, are far richer and the model becomes much more refined when social demographic indicators are taken into account. Globally, social demographic variables demonstrate some effects on each satisfaction individually but also on the interrelation (nature of the relations) between life and work satisfaction.
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We obtain minimax lower bounds on the regret for the classicaltwo--armed bandit problem. We provide a finite--sample minimax version of the well--known log $n$ asymptotic lower bound of Lai and Robbins. Also, in contrast to the log $n$ asymptotic results on the regret, we show that the minimax regret is achieved by mere random guessing under fairly mild conditions on the set of allowable configurations of the two arms. That is, we show that for {\sl every} allocation rule and for {\sl every} $n$, there is a configuration such that the regret at time $n$ is at least 1 -- $\epsilon$ times the regret of random guessing, where $\epsilon$ is any small positive constant.
Resumo:
Most research on single machine scheduling has assumedthe linearity of job holding costs, which is arguablynot appropriate in some applications. This motivates ourstudy of a model for scheduling $n$ classes of stochasticjobs on a single machine, with the objective of minimizingthe total expected holding cost (discounted or undiscounted). We allow general holding cost rates that are separable,nondecreasing and convex on the number of jobs in eachclass. We formulate the problem as a linear program overa certain greedoid polytope, and establish that it issolved optimally by a dynamic (priority) index rule,whichextends the classical Smith's rule (1956) for the linearcase. Unlike Smith's indices, defined for each class, ournew indices are defined for each extended class, consistingof a class and a number of jobs in that class, and yieldan optimal dynamic index rule: work at each time on a jobwhose current extended class has larger index. We furthershow that the indices possess a decomposition property,as they are computed separately for each class, andinterpret them in economic terms as marginal expected cost rate reductions per unit of expected processing time.We establish the results by deploying a methodology recentlyintroduced by us [J. Niño-Mora (1999). "Restless bandits,partial conservation laws, and indexability. "Forthcomingin Advances in Applied Probability Vol. 33 No. 1, 2001],based on the satisfaction by performance measures of partialconservation laws (PCL) (which extend the generalizedconservation laws of Bertsimas and Niño-Mora (1996)):PCL provide a polyhedral framework for establishing theoptimality of index policies with special structure inscheduling problems under admissible objectives, which weapply to the model of concern.
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The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375-381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727-732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.
Resumo:
Introduction: Different routes of postoperative analgesia may be used after cesarean section: systemic, spinal or epidural [1]. Although the efficacy of these alternative analgesic regimen has already been studied [2, 3], very few studies have compared patients' satisfaction between them. Methodology: After ethical committee acceptation, 100 ASA 1 patients scheduled for an elective cesarean section were randomized in 4 groups. After a standardized spinal anesthesia (hyperbaric bupivacaine 10 mg and fentanyl 20 μg), each group had a different postoperative analgesic regimen: - Group 1: oral paracetamol 4x1 g/24 h, oral ibuprofene 3x600 mg/24 h and subcutaneous morphine on need (0.1 mg/kg 6x/24 h) - Group 2: intrathecal morphine (100 μg) and then same as Group 1 - Group 3: oral paracetamol 4x1 g/24 h, oral ibuprofene 3x600 mg/24 h and PCEA with fentanyl 5 μg/ml epidural solution - Group 4: oral paracetamol 4x1g/24 h, oral ibuprofene 3x600 mg/ 24 h and PCEA with bupivacaine 0.1% and fentanyl 2 μg/ml epidural solution After 48 hours, a specific satisfaction questionnaire was given to all patients which permitted to obtain 2 different scores concerning postoperative analgesia: a global satisfaction score (0-10) and a detailed satisfaction score (5 questions scored 0-10 with a summative score of 0-50). Both scores, expressed as mean ± SD, were compared between the 4 groups with a Kruskall-Wallis test and between each group with a Mann-Whitney test. A P-value <0.05 was considered significant. Results: Satisfaction scores Gr. 1 (n = 25) Gr. 2 (n = 25) Gr. 3 (n = 25) Gr. 4 (n = 25) P-value global (0-10) 8.2 ± 1.2 9.0 ± 1.0 7.8 ± 2.1 6.5 ± 2.5 0.0006 detailed (0-50) 40 ± 6 43 ± 5 38 ± 6 34 ± 8 0.0002 Conclusion: Satisfaction scores were significantly better in patients who received a systemic postoperative analgesia only (Groups 1 and 2) compared to patients who received systemic and epidural postoperative analgesia (Groups 3 and 4). The best scores were achieved with the combination of intrathecal morphine and multimodal systemic analgesia (Group 2) which allowed early ambulation without significant pain. Patients treated with postoperative epidural analgesia with combined local anesthetics and opioids (Group 4) obtained the worse scores (more restrictive nursing with less mobility, frequent asymmetrical block with insufficient analgesia on one side and motor block on the other)