Application of Lagrangian relaxation to computer network control

AbstractThe problem of routing and flow control in a computer communication network is formulated as a mixed integer nonlinear programming problem. The Lagrangian relaxation method is used to decompose the problem into subproblems that are relatively easier to solve than the original problem. An algorithm is then developed which can obtain an optimal solution to the problem

A high-level computing algorithm for diverging and converging branch nonserial dynamic programming systems

AbstractWe present high-level computing algorithms for efficiently processing the diverging and converging branch systems in nonserial dynamic programming. A special technique in devised for processing the network functions such that the minimum amount of storage is employed. It is shown that if k is the discretization level of the state and decision variables then the space complexities are O(k) and O(k2) for the diverging and converging branch systems, respectively. The resultant time complexities are also developed. These savings in computational complexities enhance the attractiveness of dynamic programming as a tool for processing more complex nonserial systems

Flood plain management, water quality management, mathematical models

Issued as Report, Technical progress reports [nos. 1-5], and Technical completion report, Project no. E-24-65

Cluster validity for fuzzy criterion clustering

AbstractIn this paper, we define a validity measure for fuzzy criterion clustering which is a novel approach to fuzzy clustering that in addition to being non-distance-based, addresses the cluster validity problem. The model is then recast as a bilevel fuzzy criterion clustering problem. We propose an algorithm for this model that solves both the validity and clustering problems. Our approach is validated via some sample problems

Workshop on dynamic programming and water resources

Issued as Proceedings and Final report, Project no. E-24-64