Optimization of an Operational Waste Valorization Investment Portfolio in Copper Mining: An ε-Constraint Approach

The mining industry generates substantial volumes of operational waste, including lubricant oils, lead-acid batteries, steel scrap, and end-of-life tires (ELTs). Their valorization is increasingly required under Extended Producer Responsibility (EPR) frameworks, but Centre for Innovation in Technology and Design of Materials for the Built Environment—CIMAC_ANID CTI250005 investment decisions are constrained by limited capital and competing sustainability objectives. This study proposes a dynamic Mixed-Integer Linear Programming (MILP) model to optimize a multi-waste valorization investment portfolio for the copper industry. The model maximizes Net Present Value (NPV) over a multi-period horizon while satisfying EPR targets, capital constraints, and sustainability requirements. Using the ε-constraint method, it quantifies trade-offs between economic performance and social value by incorporating permanent local employment as a binding constraint. Applied to a single case study of a Chilean SX–EW plant, the model selects an Oil Filtration Plant, a Scrap Recycling Yard, and an ELT Pyrolysis Plant, achieving a maximum NPV of USD 5.363 million. Sensitivity analysis of the employment target identifies three decision zones: up to 18 jobs, the target is not binding and the NVP-optimal portfolio is unchanged; between 19 and 26 jobs, the Battery Processing Plant must also be built, reducing NPV by approximately USD 0.49 million (9%); above 26 jobs, the problem becomes infeasible. The framework integrates economic, environmental, and social dimensions, providing a decision-support tool for EPR compliance and sustainable waste valorization planning.

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Publication Details

Journal
Minerals
Published
2026-11-01
DOI
https://doi.org/10.3390/min16111138
Primary Topic
Mining Techniques and Economics
Type
article
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article

Optimization of an Operational Waste Valorization Investment Portfolio in Copper Mining: An ε-Constraint Approach

Vinka Monardes, Andrea Teresa Espinoza Pérez, Juan M. Sepúlveda, Iván Dérpich et al.
Minerals
Mining Techniques and Economics
article

Optimization of an Operational Waste Valorization Investment Portfolio in Copper Mining: An ε-Constraint Approach

Vinka Monardes, Andrea Teresa Espinoza Pérez, Juan M. Sepúlveda, Iván Dérpich, Cristóbal Leyton-Urzúa, Melisa Herrera
article en

Abstract

The mining industry generates substantial volumes of operational waste, including lubricant oils, lead-acid batteries, steel scrap, and end-of-life tires (ELTs). Their valorization is increasingly required under Extended Producer Responsibility (EPR) frameworks, but Centre for Innovation in Technology and Design of Materials for the Built Environment—CIMAC_ANID CTI250005 investment decisions are constrained by limited capital and competing sustainability objectives. This study proposes a dynamic Mixed-Integer Linear Programming (MILP) model to optimize a multi-waste valorization investment portfolio for the copper industry. The model maximizes Net Present Value (NPV) over a multi-period horizon while satisfying EPR targets, capital constraints, and sustainability requirements. Using the ε-constraint method, it quantifies trade-offs between economic performance and social value by incorporating permanent local employment as a binding constraint. Applied to a single case study of a Chilean SX–EW plant, the model selects an Oil Filtration Plant, a Scrap Recycling Yard, and an ELT Pyrolysis Plant, achieving a maximum NPV of USD 5.363 million. Sensitivity analysis of the employment target identifies three decision zones: up to 18 jobs, the target is not binding and the NVP-optimal portfolio is unchanged; between 19 and 26 jobs, the Battery Processing Plant must also be built, reducing NPV by approximately USD 0.49 million (9%); above 26 jobs, the problem becomes infeasible. The framework integrates economic, environmental, and social dimensions, providing a decision-support tool for EPR compliance and sustainable waste valorization planning.

MineralsVol. 16(11)
Universidad de Santiago de Chile (CL), Universidad de Antofagasta (CL)
Openalex Percentile: Top 17%
Mining Techniques and Economics
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