4.5 Article

Fitness-Based Acceleration Coefficients Binary Particle Swarm Optimization (FACBPSO) to Solve the Discounted Knapsack Problem

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Theory & Methods

A binary moth search algorithm based on self-learning for multidimensional knapsack problems

Yanhong Feng et al.

Summary: This study focuses on the importance of population diversity in the moth search algorithm and proposes a binary moth search algorithm based on self-learning to address the limitations of the original algorithm. The new algorithm shows effectiveness in solving combinatorial optimization problems and demonstrates good performance in experiments.

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE (2022)

Article Computer Science, Artificial Intelligence

Set Theory-Based Operator Design in Evolutionary Algorithms for Solving Knapsack Problems

Ran Wang et al.

Summary: This article introduces the solution transformation process based on set theory, proposes ideas for improving the transformation process, and suggests new operators for KPs. Experimental results demonstrate the superiority of the proposed operators.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2021)

Article Energy & Fuels

An Improved Particle Swarm Optimization with Chaotic Inertia Weight and Acceleration Coefficients for Optimal Extraction of PV Models Parameters

Arooj Tariq Kiani et al.

Summary: The paper proposes an improved PSO algorithm by introducing chaotic strategies to control inertia weight and acceleration coefficients, effectively estimating the parameters of PV modules and cells. The proposed method avoids some issues of traditional PSO and achieves good performance in practical systems.

ENERGIES (2021)

Article Computer Science, Interdisciplinary Applications

A Binary Equilibrium Optimization Algorithm for 0-1 Knapsack Problems

Mohamed Abdel-Basset et al.

Summary: A binary version of equilibrium optimization (BEO) is proposed for solving the 0-1 knapsack problem, with the study showing that the choice of transfer function plays a crucial role in the performance of binary algorithms. V-Shaped V3 transfer function is identified as the best, while sigmoid S3 transfer function can benefit the performance of other algorithms.

COMPUTERS & INDUSTRIAL ENGINEERING (2021)

Article Computer Science, Artificial Intelligence

Particle Swarm Optimization Based on a Novel Evaluation of Diversity

Haohao Zhou et al.

Summary: This paper introduces a new variant of particle swarm optimization, PSO-ED, which efficiently evaluates swarm diversity, proposes a concept of exploration degree, and a disturbance update mode. PSO-ED demonstrates excellent performance on the CEC2015 test suite, achieving six best results.

ALGORITHMS (2021)

Article Computer Science, Artificial Intelligence

Solving discounted {0-1} knapsack problems by a discrete hybrid teaching-learning-based optimization algorithm

Congcong Wu et al.

APPLIED INTELLIGENCE (2020)

Article Computer Science, Artificial Intelligence

A novel discrete whale optimization algorithm for solving knapsack problems

Ya Li et al.

APPLIED INTELLIGENCE (2020)

Article Mathematics, Interdisciplinary Applications

A Discrete Particle Swarm Optimization to Solve the Put-Away Routing Problem in Distribution Centres

Rodrigo Andres Gomez-Montoya et al.

COMPUTATION (2020)

Article Engineering, Electrical & Electronic

A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem

Ernesto Cipriani et al.

SMART CITIES (2020)

Article Automation & Control Systems

Low-Complexity Tracking Control of Strict-Feedback Systems With Unknown Control Directions

Jin-Xi Zhang et al.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2019)

Article Computer Science, Artificial Intelligence

Multi-strategy monarch butterfly optimization algorithm for discounted {0-1} knapsack problem

Yanhong Feng et al.

NEURAL COMPUTING & APPLICATIONS (2018)

Article Operations Research & Management Science

Easy knapsacks and the complexity of energy allocation problems in the smart grid

Theo Karaboghossian et al.

OPTIMIZATION LETTERS (2018)

Article Computer Science, Information Systems

Binary Moth Search Algorithm for Discounted {0-1} Knapsack Problem

Yan-Hong Feng et al.

IEEE ACCESS (2018)

Article Automation & Control Systems

An Accelerated Convergent Particle Swarm Optimizer (ACPSO) of Multimodal Functions

Yasir Mehmood et al.

INTELLIGENT AUTOMATION AND SOFT COMPUTING (2018)

Proceedings Paper Computer Science, Information Systems

Fitness-based Acceleration Coefficients to Enhance the Convergence Speed of Novel Binary Particle Swarm Optimization

Yasir Mehmood et al.

2018 INTERNATIONAL CONFERENCE ON FRONTIERS OF INFORMATION TECHNOLOGY (FIT 2018) (2018)

Article Computer Science, Artificial Intelligence

Discrete differential evolutions for the discounted {0-1} knapsack problem

Hong Zhu et al.

INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION (2017)

Article Computer Science, Information Systems

Exact and approximate algorithms for discounted {0-1} knapsack problem

Yi-Chao He et al.

INFORMATION SCIENCES (2016)

Article Computer Science, Interdisciplinary Applications

Algorithms for randomized time-varying knapsack problems

Yichao He et al.

JOURNAL OF COMBINATORIAL OPTIMIZATION (2016)

Article Computer Science, Artificial Intelligence

A fuzzy hybrid project portfolio selection method using Data Envelopment Analysis, TOPSIS and Integer Programming

Madjid Tavana et al.

EXPERT SYSTEMS WITH APPLICATIONS (2015)

Article Mathematics, Applied

Dynamic programming based algorithms for the discounted {0-1} knapsack problem

Aiying Rong et al.

APPLIED MATHEMATICS AND COMPUTATION (2012)

Article Computer Science, Information Systems

Fusing ant colony optimization with Lagrangian relaxation for the multiple-choice multidimensional knapsack problem

Zhi-gang Ren et al.

INFORMATION SCIENCES (2012)