A comprehensive empirical demonstration of the impact of choice constraints on solving generalizations of the 0–1 knapsack problem using the integer programming option of CPLEX®

DOI10.1080/0305215X.2019.1658748OpenAlexW2972694565MaRDI QIDQ5059432

Francis J. Vasko, Yun Lu

Publication date: 23 December 2022

Published in: Engineering Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/0305215x.2019.1658748

zbMATH Keywords

multidimensional knapsack problemmultiple-choice multidimensional knapsack problemCPLEX\(^{\circledR}\) integer programming optionmulti-demand multidimensional knapsack problemmulti-demand multiple-choice multidimensional knapsack problem

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Related Items (2)

Simple strategies that generate bounded solutions for the multiple‐choice multi‐dimensional knapsack problem: a guide for OR practitioners ⋮ When to use Integer Programming Software to solve large multi-demand multidimensional knapsack problems: a guide for operations research practitioners

Uses Software

• CPLEX
• OR-Library
• Knapsack

Cites Work

• Unnamed Item
• Bethlehem steel combines cutting stock and set covering to enhance customer service
• A genetic algorithm for the multidimensional knapsack problem
• A real-time one-dimensional cutting stock algorithm for balanced cutting patterns
• A minimal algorithm for the multiple-choice knapsack problem
• A hierarchical approach for one-dimensional cutting stock problems in the steel industry that maximizes yield and minimizes overgrading
• A brief history of linear and mixed-integer programming computation
• First-level tabu search approach for solving the multiple-choice multidimensional knapsack problem
• Adaptive memory search for multidemand multidimensional knapsack problems
• A Local-Search-Based Heuristic for the Demand-Constrained Multidimensional Knapsack Problem

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