<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Modified Social Forces Algorithm: from Pedestrian Dynamic to Metaheuristic Optimization</dcterms:title><dcterms:identifier>https://doi.org/10.34820/FK2/7GFPBU</dcterms:identifier><dcterms:creator>Purba Daru Kusuma</dcterms:creator><dcterms:creator>Dimas Adiputra</dcterms:creator><dcterms:publisher>Telkom University Dataverse</dcterms:publisher><dcterms:issued>2022-07-14</dcterms:issued><dcterms:modified>2022-07-14T12:13:30Z</dcterms:modified><dcterms:description>This work proposes a new simple metaheuristic optimization method inspired by the social forces model used in pedestrian dynamics. The proposed model is a swarm-based model where a collective intelligence is shared  among the agents, consisting of several persons or agents who walk over the search space to find the best solution.</dcterms:description><dcterms:subject>Computer and Information Science</dcterms:subject><dcterms:isReferencedBy>P. D. Kusuma and D. Adiputra, "Modified Social Forces Algorithm: from Pedestrian Dynamic to Metaheuristic Optimization", International Journal of Intelligent Engineering and Systems, 15(3), 294-303, 2022., doi, 10.22266/ijies2022.0630.25</dcterms:isReferencedBy><dcterms:contributor>DARU KUSUMA, PURBA</dcterms:contributor><dcterms:dateSubmitted>2022-07-14</dcterms:dateSubmitted><dcterms:license>CC0</dcterms:license><dcterms:rights>CC0 Waiver</dcterms:rights></metadata>