Algorithmic Solutions to Some Transportation Optimization Problems with Applications in the Metallurgical Industry

TL;DR

This paper introduces novel polynomial-time algorithms for transportation optimization problems with practical applications in the metallurgical industry, focusing on cost and resource minimization in structured networks.

Contribution

It presents new algorithmic solutions and extensions for constrained transportation problems with practical industry applications, considering multiple optimization objectives.

Findings

Algorithms are optimal or nearly optimal for structured networks.

Applicable to real-world problems in mining, metallurgical, and communication industries.

Addresses multiple objectives like cost and resource minimization.

Abstract

In this paper we address several constrained transportation optimization problems (e.g. vehicle routing, shortest Hamiltonian path), for which we present novel algorithmic solutions and extensions, considering several optimization objectives, like minimizing costs and resource usage. All the considered problems are motivated by practical situations arising, for instance, in the mining and metallurgical industry or in data communication. We restrict our attention to transportation networks with path, tree or geometric structures, for which the developed polynomial-time algorithms are optimal or nearly optimal.