A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications

This paper comprehensively explains how to solve mixed-integer nonlinear programming (MINLP) models using the generalized benders decomposition (GBD) method. The MINLP problem is an optimization model in which some variables must be integers and the objective function or constraints are nonlinear. ...

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Main Authors: Fadiah Hasna Nadiatul Haq, Diah Chaerani, Anita Triska
Format: Article
Language:English
Published: Mathematics Department UIN Maulana Malik Ibrahim Malang 2024-11-01
Series:Cauchy: Jurnal Matematika Murni dan Aplikasi
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Online Access:https://ejournal.uin-malang.ac.id/index.php/Math/article/view/29398
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author Fadiah Hasna Nadiatul Haq
Diah Chaerani
Anita Triska
author_facet Fadiah Hasna Nadiatul Haq
Diah Chaerani
Anita Triska
author_sort Fadiah Hasna Nadiatul Haq
collection DOAJ
description This paper comprehensively explains how to solve mixed-integer nonlinear programming (MINLP) models using the generalized benders decomposition (GBD) method. The MINLP problem is an optimization model in which some variables must be integers and the objective function or constraints are nonlinear.  The GBD method is an extension of the Benders Decomposition (BD) method, effectively handles the characteristics of the MINLP  model, where the model has nonlinear properties and involves two types of variables, namely continuous variables and integer variables. The GBD method decomposes the problem into primal and master problems that are solved alternately until the optimal solution is found. The main difference between the GBD and BD methods is that GBD uses nonlinear duality in the main problem so that GBD can solve the nonlinear problem, whereas BD applies linear duality. This paper also presents some theorem proofs related to GBD that were not presented in detail in the previous literature. The application of the GBD method is also presented to demonstrate how the method can be effectively used to solve real-world MINLP problems.
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spelling doaj-art-27b0ed18fa6949fc8a9285acb7af081a2025-08-20T02:13:45ZengMathematics Department UIN Maulana Malik Ibrahim MalangCauchy: Jurnal Matematika Murni dan Aplikasi2086-03822477-33442024-11-019232934010.18860/ca.v9i2.293988271A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and ApplicationsFadiah Hasna Nadiatul Haq0Diah Chaerani1Anita Triska2Department of Mathematics, Universitas Padjadjaran, Jl. Raya Bandung Sumedang KM 21, Sumedang, IndonesiaDepartment of Mathematics, Universitas Padjadjaran, Jl. Raya Bandung Sumedang KM 21, Sumedang, IndonesiaDepartment of Mathematics, Universitas Padjadjaran, Jl. Raya Bandung Sumedang KM 21, Sumedang, IndonesiaThis paper comprehensively explains how to solve mixed-integer nonlinear programming (MINLP) models using the generalized benders decomposition (GBD) method. The MINLP problem is an optimization model in which some variables must be integers and the objective function or constraints are nonlinear.  The GBD method is an extension of the Benders Decomposition (BD) method, effectively handles the characteristics of the MINLP  model, where the model has nonlinear properties and involves two types of variables, namely continuous variables and integer variables. The GBD method decomposes the problem into primal and master problems that are solved alternately until the optimal solution is found. The main difference between the GBD and BD methods is that GBD uses nonlinear duality in the main problem so that GBD can solve the nonlinear problem, whereas BD applies linear duality. This paper also presents some theorem proofs related to GBD that were not presented in detail in the previous literature. The application of the GBD method is also presented to demonstrate how the method can be effectively used to solve real-world MINLP problems.https://ejournal.uin-malang.ac.id/index.php/Math/article/view/29398optimizationmixed-integer nonlinear programminggeneralized benders decomposition
spellingShingle Fadiah Hasna Nadiatul Haq
Diah Chaerani
Anita Triska
A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications
Cauchy: Jurnal Matematika Murni dan Aplikasi
optimization
mixed-integer nonlinear programming
generalized benders decomposition
title A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications
title_full A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications
title_fullStr A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications
title_full_unstemmed A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications
title_short A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications
title_sort generalized benders decomposition for mixed integer nonlinear programming theory and applications
topic optimization
mixed-integer nonlinear programming
generalized benders decomposition
url https://ejournal.uin-malang.ac.id/index.php/Math/article/view/29398
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