Vehicle routing for municipal waste c o l l e c t i o n encompasses a v a r i e t y of problems. we have developed for solving some of these problems.

There have been a multitude of heuristic algorithms proposed for the solution of large scale traveling salesman problems. Our intent in this paper is to examine some of these well known heuristics, to introduce some new heuristics, and to compare these approximate techniques on the basis of efficiency and accuracy. We emphasize the strengths and weaknesses of each algorithm tested. One of our major conclusions is that it is not difficult to get within 2–3% of optimality using a composite heuristic which requires on the order of n3 computations where n is the number of nodes in the network.

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In today's information-based economy, organizations must avoid costly information security breaches. Unfortunately, organizations cannot make all of their information 100% secure all of the time. There are economic, as well as technical, impediments that prevent perfect information security. Accordingly, organizations usually prepare an annual fixed (limited) budget for the maintenance and improvement of their information security systems. Two key issues confront the chief information security officer (CISO) of an organization: how to spend this limited information security budget most effectively, and how to make the case to the organization's chief financial officer (CFO) for an increase in funds to further enhance the organization's information security. The primary objective of this article is to show how to use the analytic hierarchy process (AHP) to address these two information security issues.

This paper considers a class of network optimization problems in which certain diracd arcs must be covered by a set of cycles. Our study was motivated by a distribution planning proMan of a commaaal firm that had to make delivaies o m several origindestination pairs (directed arcs) and that could service any demand arc by using a vehicle in its own fleet or by paying a common carrier. The problem is to determine an optimal fleet size and the resulting vehicle routes while satisfying maximum route-time restrictions. We formulate the problem, describe some approximate solution strategies. and discuss important implementation issues.Subjut Areas: Lofitiu and Distribution, HrurLrrlcs. and Networks.