Route Planning

Maintaining a low-cost route structure that meets both business constraints and customer service requirements is critical to the success of a demand-driven supply chain.

For supply chain management (SCM), route planning is what you need to create the most efficient logistical routing plans to obtain the best results in asset utilisation and cost cutting. It is used to manage private/dedicated fleets and preserve a fine balance between controlling costs and providing excellent customer service. Its tactical route planning is employed to create sales ter­ritories and balance the transportation workload across multiple days. Supply chain management route planning helps companies to

  • Decrease transportation and route costs
  • Improve customer service
  • Increase the quality of routes with reduced cross-over miles and reduced miles

SCM route planning offers sophisticated optimization, analysis and scheduling tools for choosing among a myriad of available options. It helps your team build the best daily routes for private or dedicated fleets and determine master routes, routing strategies, sales territories, service frequencies and fleet sizing, as well as analyze cost, service and profitability trade-offs. It allows you to determine the optimal route mix through route schedule construction, route schedule enhancement, asset minimization, zone design, vehicle events, service technicians and dynamic sourcing.

The routing problem refers to the problem of selecting a sequence of links on a network in a particular order. In determining the sequence of locations visited by a distribution vehicle, the routing problem is best dealt with as a discrete problem, since the many constraints to do with pre­cedence and vehicle coverage are simple to express as constraints on routes constructed in a finite dimensional search domain. The other constraints, such as the total capacity of vehicles and time- related constraints, can be expressed as linear conditions on some appropriate variables, but can equally well be imposed on proposed solutions during a search procedure.

One of the best-known routing problems is the travelling salesman problem (TSP). The con­straints of this problem are that a tour must include a number of cities, visiting each city exactly once and returning to the starting city, so that the total intercity travel cost or distance is minimum. It is possible to tackle the problem using linear inequalities (on integer-constrained variables), and then try to solve the problem through simplex-like techniques exploiting the polyhedral struc­ture. Another commonly known problem is the vehicle routing problem (VRP). The VRP seeks to allocate some vehicles, starting from a depot to a set of demand locations, and minimize costs while satisfying other constraints (typically, total length of each tour or capacity constraints on vehicles). For these problems, one basic idea is to construct reasonable tours and then modify them, based on some savings through interchanging locations on the tour. This works well for many practical problems in logistics applications.

The VRP, with capacity constraints, is quite frequently encountered in practice; for exam­ple, in the weekly dispatches in multi-product, multi-location environments where a good ser­vice frequency is desired. It is quite often used in the local or secondary movement of goods, where frequent despatches, combined with several locations, to seek a cost-effective option. This is very common in delivery of perishables (such as milk, ice cream, vegetables), courier operations and so on.

The other common constraint in VRP is the time window constraint, which specifies a time interval during which a certain node must be visited. This makes optimal routing more difficult to obtain.

A routing problem for which an exact solution is easily available is the so-called shortest path problem. This relates to finding a sequence of nodes (from a given origin to a given destination) on a network for which the total cost is minimum. This can be done by a well-known constructive procedure called the Dijkstra’s algorithm. The other efficient procedure called Floyd’s algorithm is also used for finding the shortest path for all origin-destination pairs in route planning.

A problem that is perhaps peculiar to India is the Indian truck routing. The simplest version of this is to find a set of paths so that each path begins at a given root node, all the nodes in the network are covered by the paths and the sum of all the path lengths is minimized. The root node refers to the factory or the dispatching points and the other nodes are the demand locations.

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

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