Results 61 to 70 of about 15,134 (244)

A Memetic Algorithm for VLSI Floorplanning [PDF]

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2007
Floorplanning is an important problem in very large scale integrated-circuit (VLSI) design automation as it determines the performance, size, yield, and reliability of VLSI chips. From the computational point of view, VLSI floorplanning is an NP-hard problem.
Tang, Maolin, Yao, Xin
openaire   +3 more sources

Energy‐aware flexible job shop scheduling problem with nonlinear routes and position‐based learning effect

International Transactions in Operational Research, Volume 33, Issue 2, Page 860-891, March 2026.
Abstract Sustainability has become one of the main objectives in all human activities and, in particular, in manufacturing environments. In this paper, we consider the flexible job shop scheduling problem with the objective of minimizing energy consumption.
Ernesto G. Birgin, José Angel Riveaux, Débora P. Ronconi   +2 more
wiley   +1 more source

Application of Memetic Algorithms in Multi-Criteria Structural Optimization

Communications, 2017
The goal of this paper is to present new innovative algorithms for discrete structural optimization of problems involving multi-criteria objective function, which contains stress, displacement and frequency constraints. The algorithm is tested on a shell
Peter Pechac, Milan Saga, Peter Weis, Tomasz Domanski, Marcin Kubiak   +4 more
doaj   +1 more source

A Hybrid Framework for Stock Price Forecasting Using Metaheuristic Feature Selection Approaches and Transformer Models Enhanced by Temporal Embedding and Attention Pruning

Applied AI Letters, Volume 7, Issue 1, February 2026.
Workflow of the proposed hybrid BWO‐Transformer framework for stock price prediction. ABSTRACT Accurately predicting stock prices remains a major challenge in financial analytics due to the complexity and noise inherent in market data. Feature selection plays a critical role in improving both computational efficiency and predictive performance. In this
Amirhossein Malakouti Semnani, Sohrab Kordrostami, Amirhossein Refahi Sheikhani, Mohammad Hossein Moattar   +3 more
wiley   +1 more source

A Computationally Efficient Stochastic Method for Quantifying the Effects of Multi‐Surrogate Model Uncertainty on Saltwater Remediation Optimization

Water Resources Research, Volume 62, Issue 1, January 2026.
Abstract Machine learning models are highly potential to substitute computationally intensive numerical simulation models in saltwater intrusion (SWI) remediation optimization. However, uncertainty inherent in machine learning models can propagate through predictions into optimization, resulting in inaccurate solutions.
Yulu Huang, Jina Yin, Chunhui Lu
wiley   +1 more source

A Memetic Algorithm for the Vehicle Routing Problem with Cross Docking [PDF]

International Journal of Supply and Operations Management, 2015
In this paper we address the VRPCD, in which a set of homogeneous vehicles are used to transport products from the suppliers to customers via a cross-dock. The products can be consolidated at the cross-dock but cannot be stored for very long as the cross-
Sanae Larioui, Mohamed Reghioui, Abdellah El Fallahi, Kamal El Kadiri   +3 more
doaj   +2 more sources

An Efficient Evolutionary Metaheuristic for the Traveling Repairman (Minimum Latency) Problem

International Journal of Computational Intelligence Systems, 2020
In this paper we revisit the memetic evolutionary family of metaheuristics, called Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA), whose members combine Furuhashi's Bacterial Evolutionary Algorithm and various discrete local search ...
Boldizsár Tüű-Szabó, Péter Földesi, László T. Kóczy   +2 more
doaj   +1 more source

Reinforcement Learning‐Assisted Meta‐Heuristics for Scheduling Job Shops With Material Handling Robots

IET Collaborative Intelligent Manufacturing, Volume 8, Issue 1, January/December 2026.
This study addresses an integrated job shop scheduling problem with material handling robots, aiming to minimise the maximum completion time. Three meta‐heuristics, seven local search strategies and two reinforcement learning algorithms are proposed to solve the problems.
Qi Jia, Kaizhou Gao, Naiqi Wu, Ponnuthurai Nagaratnam Suganthan   +3 more
wiley   +1 more source

Simulation Optimization of the Crossdock Door Assignmnet Problem [PDF]

, 2006
The purpose of this report is to present the Crossdock Door Assignment Problem, which involves assigning destinations to outbound dock doors of Crossdock centres such that travel distance by material handling equipment is minimized. We propose a two fold
Adewunmi, Adrian, Aickelin, Uwe
core   +1 more source

Application of Metaheuristic Optimisation Methods to the Design of Guided‐Mode Resonance Filters: A Comparative Study

IET Optoelectronics, Volume 20, Issue 1, January/December 2026.
In this paper, we have reviewed six distinct metaheuristic optimisation algorithms applicable to challenging problems in electromagnetics and optics. Specifically, we applied each method to the synthesis of GMR narrowband reflection filters and performed a systematic comparative evaluation. ABSTRACT The design of optical elements often requires precise
Amirreza Asadollahzadeh, Amirali Tavakkoli‐Kakhki, Mehrdad Shokooh‐Saremi   +2 more
wiley   +1 more source