Results 1 to 10 of about 1,285 (116)

A Novel Harmony Search Algorithm Based on Teaching-Learning Strategies for 0-1 Knapsack Problems [PDF]

open access: yesThe Scientific World Journal, 2014
To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems.
Shouheng Tuo   +2 more
doaj   +2 more sources

Flexible Wolf Pack Algorithm for Dynamic Multidimensional Knapsack Problems [PDF]

open access: yesResearch, 2020
Optimization problems especially in a dynamic environment is a hot research area that has attracted notable attention in the past decades. It is clear from the dynamic optimization literatures that most of the efforts have been devoted to continuous ...
Husheng Wu, Renbin Xiao
doaj   +2 more sources

An efficient optimizer for the 0/1 knapsack problem using group counseling [PDF]

open access: yesPeerJ Computer Science, 2023
The field of optimization is concerned with determining the optimal solution to a problem. It refers to the mathematical loss or gain of a given objective function.
Yazeed Yasin Ghadi   +6 more
doaj   +3 more sources

Binary metaheuristic algorithms for 0–1 knapsack problems: Performance analysis, hybrid variants, and real-world application

open access: yesJournal of King Saud University: Computer and Information Sciences
This paper examines the performance of three binary metaheuristic algorithms when applied to two distinct knapsack problems (0–1 knapsack problems (KP01) and multidimensional knapsack problems (MKP)).
Mohamed Abdel-Basset   +5 more
doaj   +3 more sources

Application of Black Hole Algorithm for Solving Knapsack Problems [PDF]

open access: yesComputer and Knowledge Engineering, 2021
This study investigates the application of the Black Hole algorithm (BH) for solving 0–1 knapsack problems. Knapsack problem is a classic and famous problem for testing and analyzing the behavior of optimization and meta-heuristic algorithms. There is no
Abdolreza Hatamlou
doaj   +1 more source

A novel approach for solving travelling thief problem using enhanced simulated annealing [PDF]

open access: yesPeerJ Computer Science, 2021
Real-world optimization problems are getting more and more complex due to the involvement of inter dependencies. These complex problems need more advanced optimizing techniques.
Hamid Ali   +5 more
doaj   +2 more sources

Nature-inspired optimization algorithms in knapsack problem: A review [PDF]

open access: yesالمجلة العراقية للعلوم الاحصائية, 2019
Meta-heuristic algorithms have become an arising field of research in recent years. Some of these algorithms have proved to be efficient in solving combinatorial optimization problems, particularly knapsack problem.
Ghalya Tawfeeq Basheer, Zakariya Algamal
doaj   +1 more source

Quantum-Inspired Differential Evolution with Grey Wolf Optimizer for 0-1 Knapsack Problem

open access: yesMathematics, 2021
The knapsack problem is one of the most widely researched NP-complete combinatorial optimization problems and has numerous practical applications. This paper proposes a quantum-inspired differential evolution algorithm with grey wolf optimizer (QDGWO) to
Yule Wang, Wanliang Wang
doaj   +1 more source

Binary social group optimization algorithm for solving 0-1 knapsack problem [PDF]

open access: yesDecision Science Letters, 2022
In this paper, we propose the binary version of the Social Group Optimization (BSGO) algorithm for solving the 0-1 knapsack problem. The standard Social Group Optimization (SGO) is used for continuous optimization problems.
Anima Naik, Pradeep Kumar Chokkalingam
doaj   +1 more source

Projects Selection In Knapsack Problem By Using Artificial Bee Colony Algorithm

open access: yesTikrit Journal of Pure Science, 2023
One of the combinatorial optimization problems is Knapsack problem, which aims to maximize the benefit of objects whose weight not exceeding the capacity of knapsack.
Armaneesa Naaman Hasoon
doaj   +1 more source

Home - About - Disclaimer - Privacy