In this paper we develop a new method for solving Dynamic Resource Allocation Problems (DRAP) that occur in the operation of freight transportation systems. Such problems involve the allocation of resources to perform tasks over a discrete-time, dynamic network. Our particular interest is in ultra-large scale problems, that involve managing thousands of resources (such as drivers or vehicles). ...

We study networks based on virtual paths, i.e. rearrangable end-to-end transport network. Virtual paths networks are readily implemented in any network using the synchronous digital hierarchy and/or the asynchronous transfer mode. The concept and its advantages, for example cost savings, network operation simpli cation and enhanced network management capabilities, are discussed. Algorithms for ...

Automatic Dynamic Memory Management (ADMM) allows programmers to be more productive, increases system reliability and functionality. However, the true characteristics of these ADMM algorithms are known to be slow and non-deterministic. It is a well known fact that object-oriented applications tend to be dynamic memory intensive. Therefore, it is imperative that the programmers must decide wheth...

We propose a way of dealing with invasive species or pest control in agriculture. Ecosystems can be modeled via dynamical systems. For their study, it is necessary to establish possible equilibria. Even moderately complex system exhibits, general, multiple steady states. Usually, they are related each other through transcritical bifurcations, i.e., the settles different equilibrium when some bi...

The New Distribution Capability and new retailing platforms will enable airlines to respond shopping requests with bundled offers of flights ancillary services, representing an evolution from traditional, flight-focused optimization. Assembling attractive set display customers therefore represents a joint pricing assortment optimization problem in airline revenue management. In this paper, we i...

Robust methods of predicting how gene drive systems will interact with ecosystems is essential for safe deployment technology. We describe quantitative tools can reduce risk uncertainty, streamline empirical research, guide management, and promote cross-sector collaboration throughout the process technology development implementation.