Maximising Throughput in a Complex Coal Export System

TL;DR

This paper introduces a parallel genetic algorithm that optimizes the entire coal export system at Newcastle, significantly improving throughput planning efficiency over existing methods.

Contribution

The paper presents a novel parallel genetic algorithm that models activities in continuous time for integrated system throughput optimization, outperforming current solvers.

Findings

Matches or improves solutions of state-of-the-art solvers

Vastly reduces memory usage and running time

Handles practical planning horizons efficiently

Abstract

The Port of Newcastle features three coal export terminals, operating primarily in cargo assembly mode, that share a rail network on their inbound side, and a channel on their outbound side. Maximising throughput at a single coal terminal, taking into account its layout, its equipment, and its operating policies, is already challenging, but maximising throughput of the Hunter Valley coal export system as a whole requires that terminals and inbound and outbound shared resources be considered simultaneously. Existing approaches to do so either lack realism or are too computationally demanding to be useful as an everyday planning tool. We present a parallel genetic algorithm to optimise the integrated system. The algorithm models activities in continuous time, can handle practical planning horizons efficiently, and generates solutions that match or improve solutions obtained with the state-of-the-art solvers, whilst vastly outperforming them both in memory usage and running time.