Search results for "OPTIMIZATION"
showing 10 items of 2824 documents
The optimization of a maintenance policy related to a global service contract
2013
With refer to a Global Service Contract between a Service Provider and a Logistic Company, the purpose of the present paper is to develop an optimization model aimed to minimize the maintenance related total cost. In particular, such contract requires the supplying of a mandatory set of corrective maintenance services on a set of equal vehicles, in a fixed time horizon. The considered problem is formulated by a non-linear constrained mathematical model that, for large practical systems as the one herein considered, becomes difficult or very hard to solve by mathematical resolution approach. For this reason, a specific resolution approach based on a constrained genetic algorithm is herein de…
Optimization of anemia treatment in hemodialysis patients via reinforcement learning
2013
Objective: Anemia is a frequent comorbidity in hemodialysis patients that can be successfully treated by administering erythropoiesis-stimulating agents (ESAs). ESAs dosing is currently based on clinical protocols that often do not account for the high inter- and intra-individual variability in the patient's response. As a result, the hemoglobin level of some patients oscillates around the target range, which is associated with multiple risks and side-effects. This work proposes a methodology based on reinforcement learning (RL) to optimize ESA therapy. Methods: RL is a data-driven approach for solving sequential decision-making problems that are formulated as Markov decision processes (MDP…
Optimization of opioid therapy for preventing incident pain associated with bone metastases
2004
Breakthrough pain is a transitory flare of Pain superimposed on an otherwise stable pain pattern in patients treated with opioids. One form of breakthrough pain is incident pain, which is due to movement and is commonly associated with bone metastases. The development of this pain is rapid and no medication, administered "as needed," has such a rapid onset that it parallels this temporal Pattern of Pain. This study used a construct based on the prevention of this event, and implemented a new experimental paradigm. Specifically, the study determined whether increasing the opioid doses above those sufficient to control pain at rest would. reduce the occurrence of these pains. Twenty-five cons…
A flexible approach to the crossing hazards problem
2010
We propose a simple and flexible framework for the crossing hazards problem. The method is not confined to two-sample problems, but may also work with continuous exposure variables whose effect changes its sign at some time-point of the observed follow-up time. Penalized partial likelihood estimation relies upon the assumption of a smooth hazard ratio via low-rank basis splines with a conventional difference penalty to ensure smoothness, and additional ad hoc penalties to obtain restricted estimates useful in the context of crossing hazards. The framework naturally also leads to a statistical test that has good power for revealing a global effect under several alternatives, including crossi…
Tool replacement with adaptive control in a non-stationary non-periodic stochastic process
1991
Abstract The problem of optimum tool replacement is studied in the case in which tool performance is characterized by progressive decay over time following stochastic laws. A control system is assumed which detects, continuously or at fixed intervals, the service state of the tool. Assuming that the service state of the tool affects the marginal cost of production, the latter is used in order to minimize the unit production cost for an unlimited production horizon. The replacement policy proposed is able to update itself in process by means of an iterative procedure which converges to a conditioned optimum. The effectiveness of such a policy is demonstrated analytically, and illustrative ex…
A contribution to the linear programming approach to joint cost allocation: Methodology and application
2009
Abstract The linear programming (LP) approach has been commonly proposed for joint cost allocation purposes. Within a LP framework, the allocation rules are based on a marginal analysis. Unfortunately, the additivity property which is required to completely allocate joint costs fails in presence of capacity, institutional or environmental constraints. In this paper, we first illustrate that the non allocated part can be interpreted as a type of producer’s surplus. Then, by using the information contained in the Simplex tableau we propose an original two-stage methodology based on the marginal costs and the production elasticity of input factors to achieve an additive cost allocation pattern…
Beyond Viner: Smoothed Cost Curves and Co-Detetermination of Output and Production Capacity
2017
We address two problems of traditional cost functions: the discontinuity caused by the production capacity (the marginal cost abruptly becomes infinite when production capacity is reached) and the production capacity is artificially exogenous. So, we introduce a smoothed form of marginal cost function. It progressively tends to infinity when it approaches to the production capacity. Then, we prove that it is perfectly possible to determine directly output, fixed costs and production capacity simultaneously, even if this could lead to a system of equations that is not so elementary to solve because it includes a Lambert function. We also show that the smoothed cost function prevails in both …
The Dynamics of Quote Prices in an Artificial Financial Market with Learning Effects
2007
In this paper we study the evolution of bid and ask prices in an electronic financial market populated by portfolio traders who optimally choose their allocation strategy on the basis of their views about market conditions. Recently, a growing literature has investigated the consequences of learning about the returns process1. There has been an increasing interest in analyzing what are the implications of relaxing the assumption that agents hold correct expectations. In particular, it has been asked the fundamental question of understanding if typical asset-pricing anomalies (like returns predictability, and excess volatility) can be generated by a learning process about the underlying econ…
Minimising value-at-risk in a portfolio optimisation problem using a multi-objective genetic algorithm
2011
[EN] In this paper, we develop a general framework for market risk optimisation that focuses on VaR. The reason for this choice is the complexity and problems associated with risk return optimisation (non-convex and non-differential objective function). Our purpose is to obtain VaR efficient frontiers using a multi-objective genetic algorithm (GA) and to show the potential utility of the algorithm to obtain efficient portfolios when the risk measure does not allow calculating an optimal solution. Furthermore, we measure differences between VaR efficient frontiers and variance efficient frontiers in VaR-return space and we evaluate out-sample capacity of portfolios on both bullish and bearis…
Tabu search for a multi-objective routing problem
2006
Multi-objective optimization problems deal with the presence of different conflicting objectives. Given that it is not possible to obtain a single solution by optimizing all the objectives simultaneously, a common way to face these problems is to obtain a set of efficient solutions called the non-dominated frontier. In this paper, we address the problem of routing school buses with two objectives: minimize the number of buses, and minimize the longest time a student would have to stay in the bus. The trade-off in this problem is between service level, which is represented by the maximum route length, and operational cost, which is represented by the number of buses in the solution. We prese…