A survey of simulated annealing as a tool for single and multiobjective optimization
By Balram Suman, P. Kumar. Journal of the Operational Research Society, 2006
639 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/a16feb2eda008466c2b0b2b38deffecf55c0c4d9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sanghamitra Bandyopadhyay
- Ujjwal Maulik
- Seyedali Mirjalili
- Afeez Abidemi
- Emmanuel Gbenga Dada
- Kalyanmoy Deb
- Sriparna Saha
- Patrick Siarry
In Computational Theory and Mathematics
- Sanghamitra Bandyopadhyay
- Ujjwal Maulik
- Seyedali Mirjalili
- Afeez Abidemi
- Emmanuel Gbenga Dada
- Kalyanmoy Deb
- Sriparna Saha
- Patrick Siarry
In Industrial and Manufacturing Engineering
- Kalyanmoy Deb
- Fulya Altıparmak
- Patrick Siarry
- Ismail Karaoglan
- Ilhem Boussaïd
- Berna Dengiz
- Julien Lepagnot
- Imdat Kara
Citations in the corpus
- The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach (2012, background): “The SA, which stems from the simulation of the annealing of solids, is a stochastic search technique that is able to escape local optima using a probability function [55].”
- A Simulated Annealing-Based Multiobjective Optimization Algorithm: AMOSA (2008, background): “A good review of several MOSA algorithms and their comparative performance analysis can be found in [18].”
- A survey on optimization metaheuristics (2013, background): “A wide bibliography can be found in [57, 90, 152, 157, 255, 259].”
- Metaheuristic algorithms for PID controller parameters tuning: review, approaches and open problems (2022, background): “Further readings and descriptive algorithms on SA can be found in Fouskakis and Draper (2002); Suman and Kumar (2006); Eglese (1990).”