Hybrid Estimation of Distribution Algorithm for solving a Resource Level Allocation Problem in a Legal Business

Mayowa Ayodele; Konstantinia Papamichail; Geraldine Gallagher; Darren  Buckley

doi:10.1145/3319619.3326782

Hybrid Estimation of Distribution Algorithm for solving a Resource Level Allocation Problem in a Legal Business

Mayowa Ayodele, Konstantinia Papamichail, Geraldine Gallagher, Darren Buckley

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Abstract

Resource level allocation entails assigning execution times to a set of resource levels required to complete a task. This is an important problem, particularly in the services sector. We consider a realworld variant of this problem originating from a legal business. The objective considered is the maximisation of damages savings.
We apply an Estimation of Distribution Algorithm (EDA) to this problem and use a machine learning model, Random Forest, as a fitness approximation method. Thee hybrid EDA presents promising results.

Original language	English
DOIs	https://doi.org/10.1145/3319619.3326782
Publication status	Published - 13 Jul 2019
Event	GECCO 2019: The Genetic and Evolutionary Computation Conference - Prague, Czech Republic Duration: 13 Jul 2019 → 17 Jul 2019 https://gecco-2019.sigevo.org/index.html/HomePage

Conference

Conference	GECCO 2019
Country/Territory	Czech Republic
City	Prague
Period	13/07/19 → 17/07/19
Internet address	https://gecco-2019.sigevo.org/index.html/HomePage

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10.1145/3319619.3326782

Hybrid_Estimation_of_Distribution_Algorithm_for_solving_a__Resource_Level_Allocation_Problem_in_a_Legal_BusinessAccepted author manuscript, 456 KB

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title = "Hybrid Estimation of Distribution Algorithm for solving a Resource Level Allocation Problem in a Legal Business",

abstract = "Resource level allocation entails assigning execution times to a set of resource levels required to complete a task. This is an important problem, particularly in the services sector. We consider a realworld variant of this problem originating from a legal business. The objective considered is the maximisation of damages savings.We apply an Estimation of Distribution Algorithm (EDA) to this problem and use a machine learning model, Random Forest, as a fitness approximation method. Thee hybrid EDA presents promising results.",

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T1 - Hybrid Estimation of Distribution Algorithm for solving a Resource Level Allocation Problem in a Legal Business

AU - Ayodele, Mayowa

AU - Papamichail, Konstantinia

AU - Gallagher, Geraldine

AU - Buckley, Darren

PY - 2019/7/13

Y1 - 2019/7/13

N2 - Resource level allocation entails assigning execution times to a set of resource levels required to complete a task. This is an important problem, particularly in the services sector. We consider a realworld variant of this problem originating from a legal business. The objective considered is the maximisation of damages savings.We apply an Estimation of Distribution Algorithm (EDA) to this problem and use a machine learning model, Random Forest, as a fitness approximation method. Thee hybrid EDA presents promising results.

AB - Resource level allocation entails assigning execution times to a set of resource levels required to complete a task. This is an important problem, particularly in the services sector. We consider a realworld variant of this problem originating from a legal business. The objective considered is the maximisation of damages savings.We apply an Estimation of Distribution Algorithm (EDA) to this problem and use a machine learning model, Random Forest, as a fitness approximation method. Thee hybrid EDA presents promising results.

U2 - 10.1145/3319619.3326782

DO - 10.1145/3319619.3326782

M3 - Paper

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Y2 - 13 July 2019 through 17 July 2019

ER -

Hybrid Estimation of Distribution Algorithm for solving a Resource Level Allocation Problem in a Legal Business

Abstract

Conference

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