{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:56:17Z","timestamp":1777704977267,"version":"3.51.4"},"reference-count":59,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,8,11]]},"abstract":"<jats:p>Solving the shortest path problem is very difficult in situations such as emergency rescue after a typhoon: road-damage caused by a typhoon causes the weight of the rescue path to be uncertain and impossible to represent using single, precise numbers. In such uncertain environments, neutrosophic numbers can express the edge distance more effectively: membership in a neutrosophic set has different degrees of truth, indeterminacy, and falsity. This paper proposes a shortest path solution method for interval-valued neutrosophic graphs using the particle swarm optimization algorithm. Furthermore, by comparing the proposed algorithm with the Dijkstra, Bellman, and ant colony algorithms, potential shortcomings and advantages of the proposed method are deeply explored, and its effectiveness is verified. Sensitivity analysis performed using a 2020 typhoon as a case study is presented, as well as an investigation on the efficiency of the algorithm under different parameter settings to determine the most reasonable settings. Particle swarm optimization is a promising method for dealing with neutrosophic graphs and thus with uncertain real-world situations.<\/jats:p>","DOI":"10.3233\/jifs-210233","type":"journal-article","created":{"date-parts":[[2021,6,26]],"date-time":"2021-06-26T05:21:23Z","timestamp":1624684883000},"page":"1353-1373","source":"Crossref","is-referenced-by-count":5,"title":["Particle swarm optimization for the shortest path problem"],"prefix":"10.1177","volume":"41","author":[{"given":"Lehua","family":"Yang","sequence":"first","affiliation":[{"name":"College of Electronics and Information Science, Fujian Jiangxia University, Fuzhou Fujian, China"},{"name":"Research Institute for Data Analysis and Intelligent Decision Making, Fuzhou Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongmei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Foreign Languages, Fujian Jiangxia University, Fuzhou Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruipu","family":"Tan","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Science, Fujian Jiangxia University, Fuzhou Fujian, China"},{"name":"Research Institute for Data Analysis and Intelligent Decision Making, Fuzhou Fujian, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-210233_ref1","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1145\/77600.77615","article-title":"Faster algorithms for the shortest path problem","volume":"37","author":"Ahuja","year":"1990","journal-title":"Journal Of The Acm"},{"key":"10.3233\/JIFS-210233_ref2","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1142\/S0218195992000056","article-title":"On bends and lengths of rectilinear paths: a graph theoretic approach","volume":"02","author":"Yang","year":"1992","journal-title":"International Journal of Computational Geometry & Applications"},{"key":"10.3233\/JIFS-210233_ref3","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1007\/978-3-540-76290-4_18","article-title":"Fuzzy shortest path problem","volume":"222","author":"Buckley","year":"2007","journal-title":"Studia Fuzziness Soft Computing"},{"key":"10.3233\/JIFS-210233_ref4","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1016\/j.asoc.2011.11.011","article-title":"Fuzzy Dijkstra algorithm for shortest path problem under uncertain environment","volume":"12","author":"Deng","year":"2012","journal-title":"Applied Soft Computing"},{"key":"10.3233\/JIFS-210233_ref5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2013\/970197","article-title":"An algorithm for extracting intuitionistic fuzzy shortest path in a graph","volume":"2013","author":"Biswas","year":"2013","journal-title":"Applied Computational Intelligence and Soft Computing"},{"key":"10.3233\/JIFS-210233_ref6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1287\/ijoc.2018.0861","article-title":"On solving the quadratic shortest path problem","volume":"99","author":"Hu","year":"2017","journal-title":"Informs Journal On Computing"},{"key":"10.3233\/JIFS-210233_ref7","doi-asserted-by":"publisher","first-page":"1080","DOI":"10.1109\/TITS.2017.2709798","article-title":"Robust shortest path problem with distributional uncertainty","volume":"19","author":"Zhang","year":"2018","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"10.3233\/JIFS-210233_ref8","first-page":"1","article-title":"Neutrosophic Set is a Generalization of Intuitionistic Fuzzy Set, Inconsistent Intuitionistic Fuzzy Set (Picture Fuzzy Set, Ternary Fuzzy Set), Pythagorean Fuzzy Set (Atanassov\u2019s Intuitionistic Fuzzy Set of second type), q-Rung Orthopair Fuzzy Set, Spherical Fuzzy Set, and n-HyperSpherical Fuzzy Set, while Neutrosophication is a Generalization of Regret Theory, Grey System Theory, and three-Ways Decision (revisited)","volume":"29","author":"Smarandache","year":"2019","journal-title":"J N Theor"},{"key":"10.3233\/JIFS-210233_ref9","unstructured":"Smarandache F. , A unifying field in logics, Neutrosophy: Neutrosophic Probability, Set and Logic. 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