Search results for "Operations"
showing 10 items of 1692 documents
Analysis of the railway network operations safety, with of different obstacles along the route, by the study of Buffon-Laplace type problems: the cas…
2016
In this paper we use an approach based on a Buffon-Laplace type problem for an irregular hexagonal lattice and obstacles to study some problems about analysis of the railway network operations safety in the presence of different obstacles on the route.
Use of Reinforcement Learning in Two Real Applications
2008
In this paper, we present two sucessful applications of Reinforcement Learning (RL) in real life. First, the optimization of anemia management in patients undergoing Chronic Renal Failure is presented. The aim is to individualize the treatment (Erythropoietin dosages) in order to stabilize patients within a targeted range of Hemoglobin (Hb). Results show that the use of RL increases the ratio of patients within the desired range of Hb. Thus, patients' quality of life is increased, and additionally, Health Care System reduces its expenses in anemia management. Second, RL is applied to modify a marketing campaign in order to maximize long-term profits. RL obtains an individualized policy depe…
Value preserving portfolio strategies in continuous-time models
1997
We present a new approach for continuous-time portfolio strategies that relies on the principle of value preservation. This principle was developed by Hellwig (1987) for general economic decision and pricing models. The key idea is that an investor should try to consume only so much of his portfolio return that the future ability of the portfolio should be kept constant over time. This ensures that the portfolio will be a long lasting source of income. We define a continuous-time market setting to apply the idea of Hellwig to securities markets with continuous trading and examine existence (and uniqueness) of value-preserving strategies in some widely used market models. Further, we discuss…
Looking for the best modes helps solving the MRCPSP/max
2013
The multi-mode resource-constrained project scheduling problem with minimum and maximum time lags MRCPSP/max is a very general project scheduling problem with multiple execution modes per activity, renewable and non-renewable resources and minimum and maximum time lags between activities. In this paper, we describe SA-EVA, an algorithm for the problem. SA-EVA first searches for the best mode for each activity, without considering renewable resources. In this phase a simulated annealing is applied. Once a mode vector has been chosen, the problem reduces to the RCPSP/max, which SA-EVA solves with EVA, an algorithm designed in Ballestin et al. [2009. An evolutionary algorithm for the resource-…
Approximation algorithm for constrained coupled-tasks scheduling problem
2014
International audience; We tackle the makespan minimization coupled-tasks problem in presence of compatibility constraints. In particular, we focus on stretched coupled-tasks, i.e. coupled-tasks having the same sub-tasks execution time and idle time duration. In such context, we propose some complexity results according to several parameters and we design an efficient polynomial-time approximation algorithm.
An approximate/exact objective based search technique for solving general scheduling problems
2018
Abstract In this paper, we analyze single machine scheduling problems under the following minimization objectives: the maximum completion time (makespan), the total completion time and the maximum lateness, including fundamental practical aspects, which often occur in industrial or manufacturing reality: release dates, due dates, setup times, precedence constraints, deterioration (aging) of machines, as well as maintenance activities. To solve the problems, we propose an efficient representation of a solution and a fast neighborhood search technique, which calculates an approximation of criterion values in a constant time per solution in a neighborhood. On this basis, a novel approximate/ex…
Two Job Cyclic Scheduling with Incompatibility Constraints
2001
The present paper deals with the problem of scheduling several repeated occurrences of two jobs over a finite or infinite time horizon in order to maximize the yielded profit. The constraints of the problem are the incompatibilities between some pairs of tasks which require a same resource.
Time and work generalised precedence relationships in project scheduling with pre-emption: An application to the management of Service Centres
2012
Abstract In this paper we present an application of project scheduling concepts and solution procedures for the solution of a complex problem that comes up in the daily management of many company Service Centres. The real problem has been modelled as a multi-mode resource-constrained project scheduling problem with pre-emption, time and work generalised precedence relationships with minimal and maximal time lags between the tasks and due dates. We present a complete study of work GPRs which includes proper definitions, a new notation and all possible conversions amongst them. Computational results that show the efficiency of the proposed hybrid genetic algorithm and the advantages of allowi…
GENETIC AND ENVIRONMENTAL VARIATION IN PERCEIVED EXERTION AND HEART RATE DURING BICYCLE ERGOMETER WORK
1977
The relative contributions of heredity and environment to the variance in heart rate (HR) and rating of perceived exertion (RPE) during the bicycle ergometer work were studied with 14 pairs of male (6 monozygous (MZ) and 8 dizygous (DZ)) and 22 pairs of female (8 MZ and 14 DZ) twins ranging in age from 11 to 20 years. The results showed for both sexes that no significant differences in the intrapair variances of HR and RPE could be observed between the MZ and DZ twin samples. Thus it was concluded that in contrast to several other parameters of the measurements of the physical work capacity HR and RPE are not influenced to any significant degree by the genetic factors.
Online topology estimation for vector autoregressive processes in data networks
2017
An important problem in data sciences pertains to inferring causal interactions among a collection of time series. Upon modeling these as a vector autoregressive (VAR) process, this paper deals with estimating the model parameters to identify the underlying causality graph. To exploit the sparse connectivity of causality graphs, the proposed estimators minimize a group-Lasso regularized functional. To cope with real-time applications, big data setups, and possibly time-varying topologies, two online algorithms are presented to recover the sparse coefficients when observations are received sequentially. The proposed algorithms are inspired by the classic recursive least squares (RLS) algorit…