Yen's algorithm is a classical algorithm for ranking the K shortest loopless paths between a pair of nodes in a network. In this paper an implementation of Yen's algorithm is presented. Both the original algorithm and this implementation present O(Kn(m + n log n)) computational complexity order when considering a worst-case analysis. However, computational experiments are reported, which allow to conclude that in practice this new implementation outperforms two other, Perko's implementation and a straightforward one.

In the Dial-a-Ride Problem (DARP) the aim is to design vehicle routes for a set of users who must be transported between given origin and destination pairs, subject to a variety of side constraints. The standard DARP objective is cost minimization. In addition to cost, the objectives considered in this paper include three terms related to quality of service. This gives rise to a multicriteria problem. The problem is solved by means of a flexible and simple metaheuristic which efficiently integrates the reference point method for multicriteria optimization within a tabu search mechanism. Extensive tests were performed on randomly generated data and on real-life data provided by a major transporter in the Montreal area. Results indicate that the algorithm can yield a rich set of non-dominated solutions. It can also be employed to determine good trade-offs between cost and quality of service.

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This paper describes a study on the application of an algorithm to rank the K-quickest paths to the routing of data packets in Internet networks. For this purpose an experimental framework was developed by considering two types of random generated networks. To simulate values of the IP packet sizes, a truncated Pareto distribution was defined, having in mind to reflect a key feature of Internet traffic, namely its self-similar stochastic nature. Results concerning the average CPU times of the algorithm for the different sets of experiments will be presented and discussed.