Global Solution of Mixed-Integer Dynamic Optimization Problems
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Since centralized control of urban networks with detailed modeling approaches is computationally complex, developing efficient hierarchical control strategies based on aggregate modeling is of great importance. The dynamics of a heterogeneous large-scale u ...
Institute of Electrical and Electronics Engineers2015
Dynamic optimization problems affected by uncertainty are ubiquitous in many application domains. Decision makers typically model the uncertainty through random variables governed by a probability distribution. If the distribution is precisely known, then ...
In this research, two crucial optimization problems of berth allocation and yard assignment in the context of bulk ports are studied. We discuss how these problems are interrelated and can be combined and solved as a single large scale optimization problem ...
In dynamic optimization problems, the optimal input profiles are typically obtained using models that predict the system behavior. In practice, however, process models are often inaccurate, and on-line adaptation is required for appropriate prediction and ...
Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not ...
This thesis deals with models and methods for large scale optimization problems; in particular, we focus on decision problems arising in the context of seaport container terminals for the efficient management of terminal operations. Large-scale optimizatio ...
Discrete choice models are the state-of-the-art for the mathematical modeling of demand. Based on the concept of random utility, they are able to predict the choice behavior of individuals. However, these models are highly non linear and non convex in the ...
An iterative procedure for the synthesis of sparse arrays radiating focused or shaped beampattern is presented. The algorithm consists in solving a sequence of weighted l(1) convex optimization problems. The method can thus be readily implemented and effic ...
Institute of Electrical and Electronics Engineers2012
The design and operating of energy systems are key issues for matching the energy supply and consumption. Several optimization methods based on the Mixed Integer Linear Programming (MILP) have been developed for this purpose. However, due to the uncertaint ...
In many situations, agents optimize their own operations locally but their local problems are interdependent. We consider the problem of coordinating these local problems to find a globally optimal solution. We model the coordination problem as a Distribut ...