{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T11:42:56Z","timestamp":1776339776500,"version":"3.51.2"},"reference-count":94,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,9,12]],"date-time":"2020-09-12T00:00:00Z","timestamp":1599868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Simulated annealing is a well-known search algorithm used with success history in many search problems. However, the random walk of the simulated annealing does not benefit from the memory of visited states, causing excessive random search with no diversification history. Unlike memory-based search algorithms such as the tabu search, the search in simulated annealing is dependent on the choice of the initial temperature to explore the search space, which has little indications of how much exploration has been carried out. The lack of exploration eye can affect the quality of the found solutions while the nature of the search in simulated annealing is mainly local. In this work, a methodology of two phases using an automatic diversification and intensification based on memory and sensing tools is proposed. The proposed method is called Simulated Annealing with Exploratory Sensing. The computational experiments show the efficiency of the proposed method in ensuring a good exploration while finding good solutions within a similar number of iterations.<\/jats:p>","DOI":"10.3390\/a13090230","type":"journal-article","created":{"date-parts":[[2020,9,13]],"date-time":"2020-09-13T21:11:32Z","timestamp":1600031492000},"page":"230","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Simulated Annealing with Exploratory Sensing for Global Optimization"],"prefix":"10.3390","volume":"13","author":[{"given":"Majid","family":"Almarashi","sequence":"first","affiliation":[{"name":"Department of Computer Sciences and Artificial Intelligence, College of Computer Sciences and Engineering, University of Jeddah, Jeddah 21589, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1814-2643","authenticated-orcid":false,"given":"Wael","family":"Deabes","sequence":"additional","affiliation":[{"name":"Department of Computer Science in Jamoum, Umm Al-Qura University, Makkah 25371, Saudi Arabia"},{"name":"Computers and Systems Engineering Department, Mansoura University, Mansoura 35516, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4462-7070","authenticated-orcid":false,"given":"Hesham H.","family":"Amin","sequence":"additional","affiliation":[{"name":"Department of Computer Science in Jamoum, Umm Al-Qura University, Makkah 25371, Saudi Arabia"},{"name":"Department of Electrical Engineering, Computer Systems Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9936-5987","authenticated-orcid":false,"given":"Abdel-Rahman","family":"Hedar","sequence":"additional","affiliation":[{"name":"Department of Computer Science in Jamoum, Umm Al-Qura University, Makkah 25371, Saudi Arabia"},{"name":"Department of Computer Science, Faculty of Computers &amp; Information, Assiut University, Assiut 71526, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Glover, F., and Laguna, M. 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