In recent years we have evidenced an extensive effort in the development of computer communication networks. One of the important aspects of the network design process is the solution of the topological design questions involved in establishing a communication network. In this article, formulations are presented for a variety of centralized network design problems such as the minimal spanning tree problem, capacitated and degree constrained minimal spanning tree problems, The Telpak problem, and, heterogeneous network design problems. The applicability of these formulations to algorithmic development is demonstrated by developing an efficient algorithm for solving the degree constrained minimal spanning tree problem. Computational results are reported for 630 test problems. A Bender's decomposition procedure is developed and tested for the capacitated minimal spanning tree problem with less favorable results.

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The scheduling of lot sizes in multistage production environments is a fundamental problem in many Material Requirements Planning Systems. Many heuristics have been suggested for this problem with varying degrees of success. Research to date on obtaining optimal solutions has been limited to small problems. This paper presents a new formulation of the lot-sizing problem in multistage assembly systems which leads to an effective optimization algorithm for the problem. The problem is reformulated in terms of "echelon stock" which simplifies its decomposition by a Lagrangean relaxation method. A Branch and Bound algorithm which uses the bounds obtained by the relaxation was developed and tested. Computational results are reported on 120 randomly generated problems involving up to 50 items in 15 stages and up to 18 time periods in the planning horizon.MRP systems, lot sizing in MRP systems, multistage assembly systems

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Please scroll down for article-it is on subsequent pages With 12,500 members from nearly 90 countries, INFORMS is the largest international association of operations research (O.R.) and analytics professionals and students. INFORMS provides unique networking and learning opportunities for individual professionals, and organizations of all types and sizes, to better understand and use O.R. and analytics tools and methods to transform strategic visions and achieve better outcomes. For more information on INFORMS, its publications, membership, or meetings visit http://www.informs.org

The multi-resource generalized assignment problem is encountered when a set of tasks have to be assigned to a set of agents in a way that permits assignment of multiple tasks to an agent subject to the availability of a set of multiple resources consumed by that agent. This problem differs from the generalized assignment problem in that an agent consumes not just one but a variety of resources in performing the tasks assigned to him. This paper develops effective solution procedures for the multi-resource generalized assignment problem. Various relaxations of the problem are studied and theoretical relations among these relaxations are pointed out. Rules for reducing problem size are discussed and are shown to be effective through computational experiments. Heuristic solution procedures and an efficient branch and bound procedure are developed. Results of computational experiments testing these procedures are reported.combinatorial optimization, Lagrangian relaxation, subgradient optimization, generalized assignment problem

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A new formulation of the time-dependent salesman problem is presented which uses n3 variables and only n constraints.