Multi-objective approaches for the open-pit mining operational planning problem

Coelho, Vitor Nazário; Souza, Marcone Jamilson Freitas; Coelho, Igor Machado; Guimarães, Frederico Gadelha; Lust, Thibault; Cruz, Raphael Carlos

doi:10.1016/j.endm.2012.10.031

Cited by 23 publications

(9 citation statements)

References 7 publications

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“…These constraints define key aspects of the operating environment. These constraints represent the limits of chemical quality deviation defined by equations (6) -(7); production limits for each pit defined by equations (8) -(9); ore/waste ratio limits defined by equations (10) - (11); compatibility between shovel and truck defined by equation (12); and non-negativity defined by equations (13) - (14) and model validity constraints defined by equation (15).…”

Section: Mathematical Modelmentioning

confidence: 99%

“…All works present some kind of constraint, although not all of them present their mathematical formulation. Finally, it is also interesting to observe that only references [14] and [9] address the problem using a multi-objective methodology: all others, despite considering more than one objective, use other techniques such as goal programming [15] or convex scalarization.…”

Section: Literature Placement Of the Proposed Mathematical Modelmentioning

confidence: 99%

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Multi-objective evolutionary algorithms for the truck dispatch problem in open-pit mining operations

Alexandre¹,

Campelo²,

Vasconcelos³

2019

Learn. Nonlin. Mod.

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This work is concerned with the efficient allocation of trucks to shovels in operation at open-pit mines. As this problem involves high-value assets, namely mining trucks and shovels, any improvement obtained in terms of operational efficiency can result in considerable financial savings. Thus, this work presents multi-objective strategies for solving the problem of dynamically allocating a heterogeneous fleet of trucks in an open-pit mining operation, aiming at maximizing production and minimizing costs, subject to a set of operational and physical constraints. Two Multi-objective Genetic Algorithms (MOGAs) were specially developed to address this problem: the first uses specialized crossover and mutation operators, while the second employs Path-Relinking as its main variation engine. Four test instances were constructed based on real open-pit mining scenarios, and used to validate the proposed methods. The two MOGAs were compared to each other and against a Greedy Heuristic (GH), suggesting of of the MOGAs as a potential strategy for solving the multi-objective truck dispatch problem for open-pit mining operations.

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Literature Placement Of the Proposed Mathematical Modelmentioning

confidence: 99%

Multi-objective evolutionary algorithms for the truck dispatch problem in open-pit mining operations

Alexandre¹,

Campelo²,

Vasconcelos³

2019

Learn. Nonlin. Mod.

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“…More recent work presented three heuristics to solve the same problem, considering a multiobjective approach. Moreover, the work does not consider a possible queue to load and unload the trucks and also does not define the order of dispatches [3].…”

Section: Previous Workmentioning

confidence: 99%

A Comparative Study of Algorithms for Solving the Multiobjective Open-Pit Mining Operational Planning Problems

Alexandre

Campelo

Fonseca

et al. 2015

Lecture Notes in Computer Science

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This work presents a comparison of results obtained by different methods for the Multiobjective Open-Pit Mining Operational Planning Problem, which consists of dynamically and efficiently allocating a fleet of trucks with the goal of maximizing the production while reducing the number of trucks in operation, subject to a set of constraints defined by a mathematical model. Three algorithms were used to tackle instances of this problem: NSGA-II, SPEA2 and an ILS-based multiobjective optimizer called MILS. An expert system for computational simulation of open pit mines was employed for evaluating solutions generated by the algorithms. These methods were compared in terms of the quality of the solution sets returned, measured in terms of hypervolume and empirical attainment function (EAF). The results are presented and discussed.

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“…This framework has been successfully applied in the literature (see Coelho et al [32]). The tests were carried out on a Pentium Core 2 Quad (Q6600), 2.4 GHZ with 8GB of RAM, with operating system Ubuntu 10.10 Kernel 2.6.32-33, and compiled by g++ 4.5.2, using the Eclipse 3.1 IDE.…”

Section: Computational Experimentsmentioning

confidence: 99%

An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints

Coelho

Grasas

Ramalhinho

et al. 2016

European Journal of Operational Research

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Distribution planning is crucial for most companies since goods are rarely produced and consumed at the same place. Distribution costs, in addition, can be an important component of the final cost of the goods. In this paper, we study a VRP variant inspired on a real case of a large distribution company. In particular, we consider a VRP with a heterogeneous fleet of vehicles that are allowed to perform multiple trips. The problem also includes docking constraints in which some vehicles are unable to serve some particular customers. Given the combinatorial nature and the size of the problem, which discard the use of efficient exact methods for its resolution, a novel heuristic algorithm is proposed. The proposed algorithm, called GILS-VND, combines Iterated Local Search (ILS), Greedy Randomized Adaptive Search Procedure (GRASP) and Variable Neighborhood Descent (VND) procedures. Our method obtains better solutions than other approaches found in the related literature, and improves the solutions used by the company leading to * Corresponding author * * Principal corresponding author

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Multi-objective approaches for the open-pit mining operational planning problem

Cited by 23 publications

References 7 publications

Multi-objective evolutionary algorithms for the truck dispatch problem in open-pit mining operations

Multi-objective evolutionary algorithms for the truck dispatch problem in open-pit mining operations

A Comparative Study of Algorithms for Solving the Multiobjective Open-Pit Mining Operational Planning Problems

An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints

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