The problem of flow management for a class of flexible manufacturing cells is considered. The cell is designed for cyclic production of one product. This product is characterized by a sequence of operations of given length and each requiring a set of resources; the problem is therefore to...

Maintaining the natural variability of a river’s flow regime is one of the most critical strategies sustaining the ecological integrity of aquatic ecosystems. This research seeks to determine the ecological flow regime for management of streamflow existing reservoirs. The ecological flow...

Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used to solve distributed optimization and control problems. This is done by translating the distributed problem into an...

We present a class of methods for distributed optimization with event-triggered communication. To this end, we extend Nesterov’s first order scheme to use event-triggered communication in a networked environment. We then apply this approach to generalize the proximal center algorithm (PCA) for...

A new algorithm for solving large-scale convex optimization problems with a separable objective function is proposed. The basic idea is to combine three techniques: Lagrangian dual decomposition, excessive gap and smoothing. The main advantage of this algorithm is that it automatically and...

Particle swarm optimization (PSO) is a population based stochastic optimization technique. PSO is similar to optimization with Genetic Algorithms (GA). In PSO, the potential solutions (particles) move through the problem space by following the current optimum particles. Experience shows that PSO...

To what extent can life protection account for observed diversities in age-specific life expectancies across individuals and over time? We provide answers via calibrated simulations of a life-cycle model where life’s end is stochastic, and age-specific mortality hazards are endogenous outcomes...

This paper discusses the theoretical and practical aspects of new methods for solving DEA problems under real-life geometrical uncertainty and probability uncertainty of sample data. The proposed minimax approach to solve problems with geometrical uncertainty of sample data involves an...

This paper establishes (i) an extension of Michel's (1990, Theorem 1) necessity result to an abstract reduced-form model, (ii) a generalization of the results of Weitzman (1973) and Ekeland and Scheinkman (1986), and (iii) a new result that is useful particularly in the case of homogeneous...

The DUALI/DUALPC software is a system for solving quadratic-linear opimal control models. DUALI (pronounced "dual-I") provides a graphical interface for both deterministic and stochastic models as well as solvers for deterministic models and for passive learning stochastic models. DUALPC...