In this paper, we state sufficiency, necessity, convergence, existence and uniqueness results for infinite horizon optimal control problems with unbounded payoffs in which the assumptions are very weak and there are no topological assumptions about the model components. We also state a sequence...

Investors typically measure an asset’s potential to diversify a portfolio by its correlations with the portfolio’s other assets, but correlation is useful only if it provides a good estimate of how an asset’s returns co-occur cumulatively with the other asset returns over the investor’s...

The effects of random environmental impacts on optimal exploitation of a fish population are investigated using both optimization and simulation, based on a discrete-time age-structured bioeconomic model. The optimization problem is solved as a non-linear programming problem in GAMS. First, a...

In this work, we solve a real-world facility location problem by means of a mixed integer linear programming model. The problem is faced by an Italian multi-utility company operating in the sector of waste management. The company works in several Italian regions to collect and treat the urban...

In this paper, we introduce and develop the theory of semimartingale optimal transport in a path dependent setting. Instead of the classical constraints on marginal distributions, we consider a general framework of path dependent constraints. Duality results are established, representing the...

Assortment optimization is an important problem in revenue management arising in industries such as online advertising, retailing and airline ticketing. We study assortment optimization under an arbitrary mixture of multi-nomial logit (MNL) models, when the universe of products is dense. In...

Robust optimization (RO) is a young and active research field that has been mainly developed in the last 15 years. RO techniques are very useful for practice and not difficult to understand for practitioners. It is therefore remarkable that real-life applications of RO are still lagging behind;...

Adjustable robust optimization (ARO) is a technique to solve dynamic (multistage) optimization problems. In ARO, the decision in each stage is a function of the information accumulated from the previous periods on the values of the uncertain parameters. This information, however, is often...

In facility layout problems, a major concern is the optimal design or remodeling of the facilities of an organization. The decision maker's objective is to arrange the facility in an optimal way, so that the interaction among functions (i.e. machines, inventories, persons) and places (i.e....

Linear Methods are often used to compute approximate solutions to dynamic models, as these models often cannot be solved analytically. Linear methods are very popular, as they can easily be implemented. Also, they provide a useful starting point for understanding more elaborate numerical...