{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:11:40Z","timestamp":1777705900337,"version":"3.51.4"},"reference-count":33,"publisher":"SAGE Publications","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,4,28]]},"abstract":"<jats:p>The optimal evacuation route in emergency evacuation can further reduce casualties. Therefore, path planning is of great significance to emergency evacuation. Aiming at the blindness and relatively slow convergence speed of ant colony algorithm path planning search, an improved ant colony algorithm is proposed by combining artificial potential field and quantum evolution theory. On the one hand, the evacuation environment of pedestrians is modeled by the grid method. Use the potential field force in the artificial potential field, the influence coefficient of the potential field force heuristic information, and the distance between the person and the target position in the ant colony algorithm to construct comprehensive heuristic information. On the other hand, the introduction of quantum evolutionary theory. The pheromone is represented by quantum bits, and the pheromone is updated by quantum revolving door feedback control. In this way, it can not only reflect the high efficiency of quantum parallel computing, but also have the better optimization ability of ant colony algorithm. A large number of simulation experiments show that the improved ant colony algorithm has a faster convergence rate and is more effective in evacuation path planning.<\/jats:p>","DOI":"10.3233\/jifs-212220","type":"journal-article","created":{"date-parts":[[2022,1,4]],"date-time":"2022-01-04T11:41:17Z","timestamp":1641296477000},"page":"5773-5788","source":"Crossref","is-referenced-by-count":10,"title":["An improved ant colony algorithm based on artificial potential field and quantum evolution theory"],"prefix":"10.1177","volume":"42","author":[{"given":"Longzhen","family":"Zhai","sequence":"first","affiliation":[{"name":"College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaohong","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"4","key":"10.3233\/JIFS-212220_ref1","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1016\/j.physa.2009.10.019","article-title":"Experiment and modeling of exit-selecting behaviors during a building evacuation","volume":"389","author":"Fang","year":"2010","journal-title":"Physica A: Statistical Mechanics and its Applications"},{"key":"10.3233\/JIFS-212220_ref2","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.cie.2015.03.012","article-title":"Optimal facility\u2013final exit assignment algorithm for building complex evacuation","volume":"85","author":"Kang","year":"2015","journal-title":"Computers & Industrial Engineering"},{"key":"10.3233\/JIFS-212220_ref3","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.ssci.2017.10.024","article-title":"Dynamic crowd evacuation approach for the emergency route planning problem: Application to case studies","volume":"102","author":"Khalid","year":"2018","journal-title":"Safety Science"},{"issue":"10","key":"10.3233\/JIFS-212220_ref4","doi-asserted-by":"crossref","first-page":"2020","DOI":"10.1080\/13658816.2017.1346795","article-title":"An artificial bee colony-based multi-objective route planning algorithm for use in pedestrian navigation at night","volume":"31","author":"Fang","year":"2017","journal-title":"International Journal of Geographical Information Science"},{"issue":"10","key":"10.3233\/JIFS-212220_ref5","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/MAES.2018.170116","article-title":"Performance comparison of particle swarm optimization and Cuckoo search for online route planning","volume":"33","author":"G\u00f3ez-S\u00e1nchez","year":"2018","journal-title":"IEEE Aerospace and Electronic Systems Magazine"},{"key":"10.3233\/JIFS-212220_ref6","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.asoc.2018.05.008","article-title":"ACO-based mobile sink path determination for wireless sensor networks under non-uniform data constraints","volume":"69","author":"Kumar","year":"2018","journal-title":"Applied Soft Computing"},{"key":"10.3233\/JIFS-212220_ref7","first-page":"1","article-title":"An extended ACO-based mobile sink path determination in wireless sensor networks","volume":"1","author":"Donta","year":"2020","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"10.3233\/JIFS-212220_ref8","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1016\/j.asoc.2018.07.050","article-title":"Routing optimization of emergency grain distribution vehicles using the immune ant colony optimization algorithm","volume":"71","author":"Zhang","year":"2018","journal-title":"Applied Soft Computing"},{"issue":"6","key":"10.3233\/JIFS-212220_ref9","first-page":"1686","article-title":"Improved pheromone secondary update and local optimization ant colony algorithm for solving tsp","volume":"37","author":"Xu","year":"2017","journal-title":"Journal of Computer Applications"},{"issue":"5","key":"10.3233\/JIFS-212220_ref10","first-page":"782","article-title":"Ant colony algorithm based on directional pheromone coordination","volume":"28","author":"Meng","year":"2013","journal-title":"Control and Decision"},{"issue":"10","key":"10.3233\/JIFS-212220_ref11","first-page":"170","article-title":"Improved Ant Colony Algorithm Based on Bacteria Foraging","volume":"40","author":"Zhang","year":"2018","journal-title":"Computer Engineering and Science"},{"issue":"5","key":"10.3233\/JIFS-212220_ref12","first-page":"952","article-title":"An Ant Colony Algorithm for Robot Path Planning","volume":"30","author":"Chen","year":"2008","journal-title":"Systems Engineering and Electronics"},{"key":"10.3233\/JIFS-212220_ref13","first-page":"436","article-title":"Ant colony optimization algorithm for robot path planning","volume":"3","author":"Brand","year":"2010","journal-title":"international conference on computer design and applications. 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