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This digital document is a journal article from Transportation Research Part E, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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This paper investigates the development and application of a general meta-heuristic, Meta-RaPS (meta-heuristic for randomized priority search), to the traveling salesman problem (TSP). The Meta-RaPS approach is tested on several established test sets. The Meta-RaPS approach outperformed most other solution methodologies in terms of percent difference from optimal. Additionally, an industry case study that incorporates Meta-RaPS TSP in a large truck route assignment model is presented. The company estimates a more than 50% reduction in engineering time and over $2.5 million annual savings in transportation costs using the automated Meta-RaPS TSP tool compared to their current method. ... Read more

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The Traveling Salesman Problem (TSP) has already been solved in the semi-optimal manners using the numbers of different methods. Among them, genetic algorithms (GA) are pre-dominating. This paper presents a new approach to solve this problem using the Simplified Bi-directional Associative Memory (sBAM), a type of Artificial Neural Network. To get a comparative idea of its performance, the same problem has been solved using a genetic algorithm. In this paper, performance has been analyzed of a TSP by Genetic Algorithm (GA) and sBAM. Finally we proved that sBAM provide real time highly faster nearly optimal solutions than the genetic algorithm. ... Read more

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This is a AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING AND MANAGEMENT report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A100293. The abstract provided by the Pentagon follows: The surveillance mission requires aircraft to fly from a starting point through defended terrain to targets and return to a safe destination (usually the starting point). The process of selecting such a flight path is known as the Mission Route Planning (MRP) Problem and is a three-dimensional, multi-criteria (fuel expenditure, time required, risk taken, priority targeting, goals met, etc.) path search. Planning aircraft routes involves an elaborate search through numerous possibilities, which can severely task the resources of the system being used to compute the routes. Operational systems can take up to a day to arrive at a solution due to the combinatoric nature of the problem. This delay is not acceptable because timeliness of obtaining surveillance information is critical in many surveillance missions. Also, the information that the software uses to solve the MRP may become invalid during computation. An effective and efficient way of solving the MRP with multiple aircraft and multiple targets is desired. One approach to finding solutions is to simplify and view the problem as a two-dimensional, minimum path problem. This approach also minimizes fuel expenditure, time required, and even risk taken. The simplified problem is then the Traveling Salesman Problem (TSP). ... Read more