INTRODUCTION

Travelling is part of daily life. The Shortest path (SP) to the given destination therefore becomes inevitable so as to minimize costs, losses in productivity, pollutions, risks etc. Shortest path problem history is difficult to trace back. One can imagine that even in very primitive (even animal societies), finding the shortest paths (for instance, to food, colony) is essential. In the past, when drivers encountered traffic congestions/delays on the road network, they had to queue up and wait until the congestions clears off before continuing in their journeys, but not so today. In recent times, technological advances in operational research and information technology have engineered a new thought to traffic management and control system using several shortest path/path-finding algorithms e.g. Dijkstra, Bellman-Ford, A*, Floyd-Washall, Backward-recursive etc. to evaluating the shortest/fastest path en route embarkation. However, to tackle real life transportation problems today, the problems are reduced to simplified mathematical routing models (i.e. operations research models) embedded in various decision support systems such as Tora, Lingo etc., which can be solved iteratively often times. These decision support systems use dynamic programming principles (that breaks complex tasks into simpler tasks easily solvable). This study illustrates the development of a simple application that runs on dynamic programming principle to show the relevance to decision support system of finding Shortest path to a destination in a road network.

1.1     BACKGROUND OF STUDY

Traffic congestions/bad roads are critical problems experienced daily on our road networks most especially in the urban areas; and thus influences the travel time of vehicles/productivitites in cases like ambulance calls, fire service calls, armed robbery attack calls, quick calls for stock supplies at business supermarkets/warehourses etc. The shortest/fastest path to the destination hitherto being inevitable to minimize these costs, losses, risks etc. The shortest path problems uses dynamic programming technology/methodology (i.e. breaking down complex tasks into simpler easy tasks to solve) to finding the shortest path to the destination. There are different types of shortest path problems namely: Shortest path from a node to a node, shortest path from a node to many nodes, shortest path from many nodes to a node and shortest path from many nodes to many nodes in some other few instances. In some applications, the shortest path between two nodes are not necessarily a direct edge but a detour through other traversals. Again, one might require not only the shortest path to a destination but a second and third shortest paths depending on the given occasion/problem.

The major technology used in this study is dynamic programming algorithms (Dijkstra, Bellman-Ford, Backward-recursive) and relational database technology (MySQL). The software developed is a collection of algorithms (a logical step-by-step procedure for solving a mathematical problem in a finite number of steps, often involving repetition of the same basic operations). The algorithms are presented (or rendered visible) to the user, by object oriented programming language (e.g. Java) utilized in the study and also must satisfy the basic properties/characteristics of dynamic programming. The user interface within the application allows interaction between the user and the Decision Support System, which embeds MySQL database instructions required to open the database, establish a connection between the database and the Java language, perform operations such as insert, update, search data etc.

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