Multi-Criteria Integer Programming Model for Route Planning in an Off-Road Combat Environment

TL;DR

This paper introduces a multi-criteria optimization model for route planning in off-road military environments, integrating environmental and tactical risk factors to support decision-making.

Contribution

It develops a mixed-integer linear programming model that combines soil trafficability and enemy engagement risks, evaluated through a detailed case study.

Findings

The model effectively quantifies trade-offs between mobility and tactical risks.

Scenario analysis shows how risk weights and vehicle properties impact route selection.

Objective function values vary significantly with different risk and vehicle parameters.

Abstract

Route planning for military vehicles is a complex decision-making problem due to the simultaneous influence of environmental trafficability and tactical risks. This paper presents an optimization model that integrates soil trafficability and risk of enemy engagement into a decision-support model for planning activities in open terrain. Although a military application is the focus of this paper, other use cases include wildfire response, agricultural operations, and off-road vehicle recreation. The routing problem is formulated as a minimum cost mixed-integer linear program over a discretized representation of the operational environment. Each node represents a location and is connected by arcs to adjacent nodes whose traversal incurs a cost derived from a composite risk function that accounts for soil strength and the proximity to known enemy activity and prior convoy routes. Environmental inputs required for evaluating soil strength are obtained by integrating external models, which estimate spatial variations in the rating cone index (RCI) across the terrain. The model is evaluated through a case study conducted at a location in northern Colorado using fine-resolution environmental data and simulated tactical conditions. Scenario analyses demonstrate how variations in risk weighting, vehicle mobility characteristics, and operational conditions influence route geometry and mission risk. The objective function values achieved varied by five orders of magnitude based on the coefficients assigned to the terms in the cost function and the vehicle properties of the scenario. The results illustrate the capability of the proposed framework to quantify trade-offs between environmental mobility constraints and tactical considerations.