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Scope and generalization of the theory of linearly constrained linear regulator

Paolo Alessandro, Elena de Santis (1999)

Kybernetika

A previous paper by the same authors presented a general theory solving (finite horizon) feasibility and optimization problems for linear dynamic discrete-time systems with polyhedral constraints. We derived necessary and sufficient conditions for the existence of solutions without assuming any restrictive hypothesis. For the solvable cases we also provided the inequative feedback dynamic system, that generates by forward recursion all and nothing but the feasible (or optimal, according to the cases)...

Stochastic performance measurement in two-stage network processes: A data envelopment analysis approach

Alireza Amirteimoori, Saber Mehdizadeh, Sohrab Kordrostami (2022)

Kybernetika

In classic data envelopment analysis models, two-stage network structures are studied in cases in which the input/output data set are deterministic. In many real applications, however, we face uncertainty. This paper proposes a two-stage network DEA model when the input/output data are stochastic. A stochastic two-stage network DEA model is formulated based on the chance-constrained programming. Linearization techniques and the assumption of single underlying factor of the data are used to construct...

Strategies for LP-based solving a general class of scheduling problems.

Laureano F. Escudero, Gloria Pérez Sáinz de Rozas (1990)

Trabajos de Investigación Operativa

In this work we describe some strategies that have been proved to be very efficient for solving the following type of scheduling problems: Assume a set of jobs is to be performed along a planning horizon by selecting one from several alternatives for doing so. Besides selecting the alternative for each job, the target consists of choosing the periods at which each component of the work will be done, such that a set of scheduling and technological constraints is satisfied. The problem is formulated...

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