Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

9-2023

Abstract

The logistical complication of long-term mine planning involves deciding the sequential extraction of materials from the mine pit and their subsequent processing steps based on geological, geometrical, and resource constraints. The net present value (NPV) of profit over the mine's lifespan usually forms the sole objective for this problem, which is considered as the NP-hard precedence-constrained production scheduling problem (PCPSP) as well. However, increased pressure for more sustainable and carbon-aware industries also calls for environmental indicators to be considered. In this paper, we enhance the generic PCPSP formulation into a multi-objective optimization (MOO) problem whereby carbon cost forms an additional objective. We apply the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to this formulation and experiment with variants to the solution generation. Our tailored application of the NSGA-II using a set of real-world inspired datasets can form an approximated Pareto front for planners to observe stipulated annual carbon emission targets. It also displays that tailored variants of the NSGA-II can produce diverse solutions that are close to the true Pareto front.

Keywords

precedence-constraint production scheduling, resource capacity optimization, multi-objective evolutionary algorithm, sustainability

Discipline

Artificial Intelligence and Robotics | Theory and Algorithms

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the Fourteenth International Conference on Computational Logistics, Berlin, Germany, 2023 September 6-8

First Page

1

Last Page

16

City or Country

ICCL

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