ITERATED INSIDE OUT: a new exact algorithm for the transportation problem

TL;DR

This paper introduces Iterated Inside Out, an exact algorithm for the transportation problem that iteratively improves solutions and outperforms existing commercial solvers and algorithms.

Contribution

The paper presents a novel iterative algorithm for the transportation problem that enhances solution quality and computational efficiency over existing methods.

Findings

Outperforms Cplex and Gurobi in computational tests

Effectively improves basic feasible solutions iteratively

Achieves faster convergence to optimal solutions

Abstract

We propose a novel exact algorithm for the transportation problem, one of the paradigmatic network optimization problems. The algorithm, denoted Iterated Inside Out, requires in input a basic feasible solution and is composed by two main phases that are iteratively repeated until an optimal basic feasible solution is reached. In the first "inside" phase, the algorithm progressively improves upon a given basic solution by increasing the value of several non-basic variables with negative reduced cost. This phase typically outputs a non-basic feasible solution interior to the constraints set polytope. The second "out" phase moves in the opposite direction by iteratively setting to zero several variables until a new improved basic feasible solution is reached. Extensive computational tests show that the proposed approach strongly outperforms all versions of network and linear programming algorithms available in the commercial solvers Cplex and Gurobi and other exact algorithms available in the literature.