rust_vrp: Solve Capacitated Vehicle Routing Problem (CVRP)

In spopt: Spatial Optimization for Regionalization, Facility Location, and Market Analysis

Solve Capacitated Vehicle Routing Problem (CVRP)

Description

Find minimum-cost routes for multiple vehicles, each with a capacity limit, to serve all customers from a depot. Uses Clarke-Wright savings heuristic with 2-opt, relocate, and swap improvement.

Usage

rust_vrp(
  cost_matrix,
  depot,
  demands,
  capacity,
  max_vehicles,
  method,
  service_times,
  max_route_time,
  balance_time,
  earliest,
  latest
)

Arguments

cost_matrix	Square cost/distance matrix (n x n)
depot	Depot index (0-based)
demands	Demand at each location (depot demand should be 0)
capacity	Vehicle capacity
max_vehicles	Maximum number of vehicles (NULL for unlimited)
method	Algorithm: "savings" (construction only) or "2-opt" (with improvement)
service_times	Optional service time at each stop (NULL for zero)
max_route_time	Optional maximum total time per route (NULL for unlimited)
balance_time	Whether to run route-time balancing phase
earliest	Optional earliest arrival times at each stop
latest	Optional latest arrival times at each stop

Value

List with vehicle assignments, visit orders, costs, and route details

spopt documentation built on April 22, 2026, 9:07 a.m.