Results 131 to 140 of about 1,727,456 (275)

Parameter optimization of tuned mass dampers via metaheuristic algorithms

, 2021
Building-like structures should be taken under control to reduce vibrations under dynamic effects such as earthquakes, to extend the useful life of building elements and to achieve goals such as life safety and comfort.
Çoşgun, TURGAY, Bekdaş, Gebrail, Nigdeli, Sinan Melih, Uzdil, Oğuz   +3 more
core  

A matheuristic for the traveling salesman problem with positional consistency constraints

International Transactions in Operational Research, EarlyView.
Abstract We propose a matheuristic for the traveling salesman problem with positional consistency constraints, where we seek to generate a set of routes with minimum total cost, in which the nodes visited in more than one route (consistent nodes) must occupy the same relative position in all routes.
Luís Gouveia, Ana Paias, Mafalda Ponte
wiley   +1 more source

A unified formulation for home healthcare routing and scheduling problems

International Transactions in Operational Research, EarlyView.
Abstract Home Healthcare is an essential component of healthcare systems, where caregivers visit patients' homes to deliver services. While presenting advantages with respect to institutional care, such as being cost‐effective and alleviating family burdens, it presents challenges in scheduling and routing caregivers efficiently.
Sara Ceschia, Francesca Da Ros, Luca Di Gaspero, Simona Mancini, Vittorio Maniezzo, Roberto Montemanni, Roberto Maria Rosati, Andrea Schaerf   +7 more
wiley   +1 more source

Automated Design of Metaheuristic Algorithms: A Survey [PDF]

Metaheuristics have gained great success in academia and practice because their search logic can be applied to any problem with available solution representation, solution quality evaluation, and certain notions of locality.
Zhao, Qi, Duan, Qiqi, Yan, Bai, Shi, Yuhui, Cheng, Shi   +4 more
core   +1 more source

Physics Based Metaheuristic Algorithms for Global Optimization

, 2015
In recent years, several optimization methods especially metaheuristic optimization methods have been developed by scientists. People have utilized power of nature to solve problems.
Alataş, Bilal, Can,Ümit
core  

Freight distribution optimization by implementing the team orienteering problem with occasional drivers

International Transactions in Operational Research, EarlyView.
Abstract This research evaluates the effectiveness of a hybrid crowdshipping system that integrates occasional drivers with traditional delivery services (OD+TD) to improve the efficiency of freight distribution. By implementing the team orienteering problem with occasional drivers model, we develop a mathematical model and an agile optimization ...
Alisson Garcia‐Herrera, Xabier A. Martin, Adrian Serrano‐Hernandez, Angel A. Juan, Javier Faulin   +4 more
wiley   +1 more source

Metaheuristic algorithms: guidelines for implementation

, 2016
This paper presents a quick review of the basic concepts and essential steps for implementing of metaheuristic algorithms. It can be therefore used as a roadmap to shed light on solving an optimization problem using a metaheuristic algorithm.
Ts. Dr. Herman Wahid
core  

Exact and metaheuristic approaches to minimizing makespan in parallel machine scheduling with conflicting jobs

International Transactions in Operational Research, EarlyView.
Abstract We address the scheduling conflicting jobs on parallel identical machines problem with makespan minimization, a classical and computationally challenging variant of parallel machine scheduling. We develop and evaluate three distinct solution methodologies: a novel constraint programming (CP) formulation, and two metaheuristics: a multi ...
Roberto Maria Rosati, Dinh Quy Ta, Minh Hoàng Hà, Andrea Schaerf   +3 more
wiley   +1 more source

A benchmark of recent population-based metaheuristic algorithms for multi-layer neural network training

, 2020
A benchmark of recent population-based metaheuristic algorithms for multi-layer neural network ...
SJ Mousavirad (10323281), G Schaefer (7811213), SMJ Jalali (14450514), I Korovin (13402548)   +3 more
core  

Deep reinforcement learning for multi‐restart metaheuristics: an environment design for a hybrid of unbiased exploratory search and covariance matrix adaptation evolution strategy

International Transactions in Operational Research, EarlyView.
Abstract Multi‐restart metaheuristics can be highly effective for complex optimization problems, yet their performance depends critically on how restarts and algorithmic parameters are selected. This paper introduces a reinforcement learning approach for managing restart‐level decisions and parameter configurations in the UES–CMA‐ES hybrid ...
Antonio Bolufé‐Röhler, Bowen Xu
wiley   +1 more source