Verifying new instances of the multidemand multidimensional knapsack problem with instance space analysis

Scherer, Matthew E.; Hill, Raymond R.; Lunday, Brian J.; Cox, Bruce A.; White, Edward D.

doi:10.1016/j.cor.2023.106477

Computers & Operations Research

2024

DOI: 10.1016/j.cor.2023.106477

|View full text |Cite

Verifying new instances of the multidemand multidimensional knapsack problem with instance space analysis

Matthew E. Scherer,

Raymond R. Hill,

Brian J. Lunday

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

An Artificial Bee Colony Algorithm for the Multidimensional Knapsack Problem

Yaghini,

Valizadeh

2024

International Journal of Applied Metaheuristic Computing

View full text Add to dashboard Cite

The Multidimensional Knapsack Problem (MDKP) stands as a prominent challenge in combinatorial optimization, with diverse applications across various domains. The Artificial Bee Colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the foraging behavior of bees. The aim of this paper is to develop an ABC with the goal of improving the solution quality in comparison to previous studies for the MDKP. In the proposed ABC algorithm, a heuristic method is presented to make employed bees. The roulette wheel and k-tournament methods are investigated for selecting employed bees by onlooker bees. For crossing over, two methods including one-point and uniform are studied. To tune the parameters, the Design of Experiment (DOE) method has been applied. The well-known benchmark test problems have been used to evaluate the proposed algorithm. The results show the absolute superiority of the solutions generated by the proposed algorithm in compared with the previous studies.

show abstract

An Artificial Bee Colony Algorithm for the Multidimensional Knapsack Problem

Yaghini,

Valizadeh

2024

International Journal of Applied Metaheuristic Computing

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Verifying new instances of the multidemand multidimensional knapsack problem with instance space analysis

Cited by 1 publication

References 30 publications

An Artificial Bee Colony Algorithm for the Multidimensional Knapsack Problem

An Artificial Bee Colony Algorithm for the Multidimensional Knapsack Problem

Contact Info

Product

Resources

About