Route Planning

For the conservation of precious fuel and saving the transportation time, route planning exercise is of utmost importance to the carrier owner. Route planning may be advisory or statutory. The advi­sory routes are those with less operational problems and shortest distance. The cost of operation of the truck on such routes is the lowest. These are basically national or state highways connected to the markets and traffic on such routes is also high. These are very attractive for the truckers because of the immense opportunities for the return freight business. The statutory routes are those, which legally prohibit the trucker to use the routes other than the designated ones. The statutory routes are designated for carrying the particular type of goods such as explosives, hazardous chemicals or inflammable materials. The other categories of routes are those used for high productivity vehicles, high-speed vehicles or extra-heavy vehicles. The statutory routes are common in developed coun­tries and quite uncommon in India.

The main objective of route planning is to cover the distance between two points with the shortest distance, ensuring operating economy resulting into lowest transportation cost. To plan a route for a truck for multiple pickups and delivery points, spread over a vast geographical area, is a challenging task. The planning task becomes complicated in case of perishable commodity having short shelf life. Generating distance matrix, which is a one-time exercise, and generating the route matrix with nodes for pickups and delivery can solve the problem. The other factor is duration of travel in case of perishable products.

Transportation Model

Linear programming is one of the most frequently used techniques of management science and it helps the decision maker to achieve an objective, which is subject to certain restrictions. The linear programming technique derives its name from the fact that the functional relationships in the mathematical model are linear. A linear programming model consists of decision variables, an objective function and model constraints. Decision variables are mathematical symbols that repre­sent level of activity. The objective function is a linear, mathematical relationship that describes the objective of the firm in terms of decision variables and will be of either maximizing or minimizing value. The model constraints are also linear in relationships with decision variables. They represent the restrictions placed on firm by the operating environments.

One of the most widely used forms of linear programming for logistics problem is network opti­mization. The distribution centres in the distribution channels are the nodes from where the goods are distributed using the transportation links across the network. The linear programming model is evolved considering, transportation cost, demand pattern and the inventory supply position.

Source: Sople V.V (2013), Logistics Management, Pearson Education India; Third edition.

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