We consider the problem of minimizing the max of two convex functions from both approximation and sensitivity point of view.This lead up to study the epiconvergence of a sequence of level sums of convex functions and the related dual problems.
The structure of solution-sets for the equation is discussed, where are given residuated functions mapping between partially-ordered sets. An algorithm is proposed which produces a solution in the event of finite termination: this solution is maximal relative to initial trial values of . Properties are defined which are sufficient for finite termination. The particular case of max-based linear algebra is discussed, with application to the synchronisation problem for discrete-event systems;...
This article studies an equilibrium search problem when jobs provided by firms can be either unskilled or skilled and when workers differing in their education level can be either low-educated or high-educated. The structure proportion of jobs affects the equilibrium which indicates a threshold that can distinguish whether the equilibrium is separating or cross-skill. In addition, the cross-skill equilibrium solution implies the high-educated workers are more likely to obtain higher pay rates than...
It is assumed that activity times in stochastic activity networks (SANs) are independent Erlang random variable (r.v.). A recurrence method of determining the th moments of the completion time is presented. Applications are provided for illustration and are used to evaluate the applicability and appropriateness of the Erlang model to represent activity network.
In this paper we derive a priori error estimates for linear-quadratic elliptic optimal control problems with finite dimensional control space and state constraints in the whole domain, which can be written as semi-infinite optimization problems. Numerical experiments are conducted to ilustrate our theory.
This paper deals with Markov decision processes (MDPs) with real state space for which its minimum is attained, and that are upper bounded by (uncontrolled) stochastically ordered (SO) Markov chains. We consider MDPs with (possibly) unbounded costs, and to evaluate the quality of each policy, we use the objective function known as the average cost. For this objective function we consider two Markov control models and . and have the same components except for the transition laws. The transition...
We extend previous results of the same authors ([11]) on the effects of perturbation in the transition probability of a Markov cost chain for discounted Markov control processes. Supposing valid, for each stationary policy, conditions of Lyapunov and Harris type, we get upper bounds for the index of perturbations, defined as the difference of the total expected discounted costs for the original Markov control process and the perturbed one. We present examples that satisfy our conditions.
For a discrete-time Markov control process with the transition probability , we compare the total discounted costs ...
This work concerns Markov decision chains with finite state and action sets. The transition law satisfies the simultaneous Doeblin condition but is unknown to the controller, and the problem of determining an optimal adaptive policy with respect to the average reward criterion is addressed. A subset of policies is identified so that, when the system evolves under a policy in that class, the frequency estimators of the transition law are consistent on an essential set of admissible state-action pairs,...
El trabajo describe dos métodos de diseño de algoritmos heurísticos para el problema de planificación de un proyecto con limitación de recursos. El primer método es constructivo: las actividades del proyecto se intentan incorporar a la secuencia posible tan pronto como lo permiten sus relaciones de precedencia, resolviendo de diversas formas los conflictos provocados por la limitación de recursos. El segundo enfoque está basado en la idea de incorporar arcos disjuntos para resolver las incompatibilidades...
We present a review of the main “global optimization” methods. The paper comprises one introduction and two parts. In the introduction, we recall some generalities about non linear constraint-less optimization and we list some classifications which have been proposed for the global optimization methods. We then describe, in the first part, various “classical” global optimization methods, most of which available long before the appearance of Simulated Annealing (a key event in this field). There...