{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:10:16Z","timestamp":1783937416162,"version":"3.55.0"},"reference-count":33,"publisher":"Emerald","issue":"10","license":[{"start":{"date-parts":[[2017,12,4]],"date-time":"2017-12-04T00:00:00Z","timestamp":1512345600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2017,12,4]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is twofold. First, to propose an operational model for aircraft maintenance routing problem (AMRP) rather than tactical models that are commonly used in the literature. Second, to develop a fast and responsive solution method in order to cope with the frequent changes experienced in the airline industry.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>Two important operational considerations were considered, simultaneously. First one is the maximum flying hours, and second one is the man-power availability. On the other hand, ant colony optimization (ACO), simulated annealing (SA), and genetic algorithm (GA) approaches were proposed to solve the model, and the upper bound was calculated to be the criteria to assess the performance of each meta-heuristic. After attempting to solve the model by these meta-heuristics, the authors noticed further improvement chances in terms of solution quality and computational time. Therefore, a new solution algorithm was proposed, and its performance was validated based on 12 real data from the EgyptAir carrier. Also, the model and experiments were extended to test the effect of the operational considerations on the profit.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The computational results showed that the proposed solution algorithm outperforms other meta-heuristics in finding a better solution in much less time, whereas the operational considerations improve the profitability of the existing model.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>The authors focused on some operational considerations rather than tactical considerations that are commonly used in the literature. One advantage of this is that it improves the profitability of the existing models. On the other hand, identifying future research opportunities should help academic researchers to develop new models and improve the performance of the existing models.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>The experiment results showed that the proposed model and solution methods are scalable and can thus be adopted by the airline industry at large.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>In the literature, AMRP models were cast with approximated assumption regarding the maintenance issue, while neglecting the man-power availability consideration. However, in this paper, the authors attempted to relax that maintenance assumption, and consider the man-power availability constraints. Since the result showed that these considerations improve the profitability by 5.63 percent in the largest case. The proposed operational considerations are hence significant. Also, the authors utilized ACO, SA, and GA to solve the model for the first time, and developed a new solution algorithm. The value and significance of the new algorithm appeared as follow. First, the solution quality was improved since the average improvement ratio over ACO, SA, and GA goes up to 8.30, 4.45, and 4.00 percent, respectively. Second, the computational time was significantly improved since it does not go beyond 3 seconds in all the 12 real cases, which is considered much lesser compared to ACO, SA, and GA.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/imds-11-2016-0475","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T07:23:24Z","timestamp":1507879404000},"page":"2142-2170","source":"Crossref","is-referenced-by-count":30,"title":["Heuristic approaches for operational aircraft maintenance routing problem with maximum flying hours and man-power availability considerations"],"prefix":"10.1108","volume":"117","author":[{"given":"Abdelrahman E.E.","family":"Eltoukhy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Felix T.S.","family":"Chan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S.H.","family":"Chung","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ben","family":"Niu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"X.P.","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","reference":[{"issue":"6","key":"key2020120413490926700_ref001","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1016\/j.cor.2010.10.011","article-title":"An ant colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows","volume":"38","year":"2011","journal-title":"Computers & Operations Research"},{"issue":"5","key":"key2020120413490926700_ref002","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1016\/j.eswa.2012.09.012","article-title":"A simulated annealing-based parallel multi-objective approach to vehicle routing problems with time windows","volume":"40","year":"2013","journal-title":"Expert Systems With Applications"},{"issue":"1","key":"key2020120413490926700_ref003","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.ejor.2013.10.066","article-title":"Operational aircraft maintenance routing problem with remaining time consideration","volume":"235","year":"2014","journal-title":"European Journal of Operational Research"},{"issue":"4","key":"key2020120413490926700_ref004","doi-asserted-by":"crossref","first-page":"7758","DOI":"10.1016\/j.eswa.2008.09.001","article-title":"Solving a vehicle routing problem with time windows by a decomposition technique and a genetic algorithm","volume":"36","year":"2009","journal-title":"Expert Systems With Applications"},{"issue":"8","key":"key2020120413490926700_ref005","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1108\/IMDS-04-2015-0155","article-title":"Managing disruption risk in express logistics via proactive planning","volume":"115","year":"2015","journal-title":"Industrial Management & Data Systems"},{"key":"key2020120413490926700_ref006","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1023\/A:1018945415148","article-title":"The aircraft rotation problem","volume":"69","year":"1997","journal-title":"Annals of Operations Research"},{"key":"key2020120413490926700_ref007","unstructured":"Cordeau, J.-F., Laporte, G., Savelsbergh, M.W.P. and Vigo, D. (2007), \u201cVehicle routing\u201d, in Cynthia, B. and Gilbert, L. (Eds), Handbooks in Operations Research and Management Science, Chapter 6, Elsevier, pp. 367-428."},{"issue":"5","key":"key2020120413490926700_ref008","doi-asserted-by":"crossref","first-page":"5787","DOI":"10.1016\/j.eswa.2010.10.053","article-title":"Ant colony optimization-based algorithm for airline crew scheduling problem","volume":"38","year":"2011","journal-title":"Expert Systems With Applications"},{"issue":"6","key":"key2020120413490926700_ref301","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1108\/IMDS-09-2016-0358","article-title":"Airline schedule planning: a review and future directions","volume":"117","year":"2017","journal-title":"Industrial Management & Data Systems"},{"issue":"4","key":"key2020120413490926700_ref009","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1016\/j.asoc.2010.04.001","article-title":"Multi-objective vehicle routing problem with time windows using goal programming and genetic algorithm","volume":"10","year":"2010","journal-title":"Applied Soft Computing"},{"issue":"2","key":"key2020120413490926700_ref010","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1287\/opre.46.2.260","article-title":"The aircraft maintenance routing problem","volume":"46","year":"1998","journal-title":"Operations Research"},{"key":"key2020120413490926700_ref011","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.cor.2014.10.012","article-title":"Solving the dynamic traveling salesman problem using a genetic algorithm with trajectory prediction: an application to fish aggregating devices","volume":"56","year":"2015","journal-title":"Computers & Operations Research"},{"issue":"4","key":"key2020120413490926700_ref012","first-page":"508","article-title":"A lifted compact formulation for the daily aircraft maintenance routing problem","volume":"47","year":"2012","journal-title":"Transportation Science"},{"key":"key2020120413490926700_ref013","first-page":"1","article-title":"Fuzzy controller design using evolutionary techniques for twin rotor MIMO system: a comparative study","volume":"2015","year":"2015","journal-title":"Computational Intelligence and Neuroscience"},{"issue":"23","key":"key2020120413490926700_ref014","doi-asserted-by":"crossref","first-page":"9077","DOI":"10.1016\/j.eswa.2015.08.026","article-title":"A fuzzy logic feedback filter design tuned with PSO for adaptive controller","volume":"42","year":"2015","journal-title":"Expert Systems with Applications"},{"issue":"8","key":"key2020120413490926700_ref015","article-title":"Invited review paper on managing disruption risk in express logistics via proactive planning","volume":"115","year":"2015","journal-title":"Industrial Management & Data Systems"},{"key":"key2020120413490926700_ref016","article-title":"Aircraft routing at American airlines","year":"1992"},{"issue":"4598","key":"key2020120413490926700_ref017","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1126\/science.220.4598.671","article-title":"Optimization by simulated annealing","volume":"220","year":"1983","journal-title":"Science"},{"issue":"4","key":"key2020120413490926700_ref018","first-page":"493","article-title":"A network-based model for the integrated weekly aircraft maintenance routing and fleet assignment problem","volume":"47","year":"2012","journal-title":"Transportation Science"},{"issue":"1","key":"key2020120413490926700_ref019","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1287\/trsc.1100.0338","article-title":"On a new rotation tour network model for aircraft maintenance routing problem","volume":"45","year":"2011","journal-title":"Transportation Science"},{"issue":"1","key":"key2020120413490926700_ref020","first-page":"19","article-title":"Simulated annealing for the multi-objective aircrew rostering problem","volume":"33","year":"1999","journal-title":"Transportation Research Part A: Policy and Practice"},{"issue":"4-5","key":"key2020120413490926700_ref021","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1111\/j.1475-3995.2000.tb00209.x","article-title":"Heuristic approaches to the asymmetric travelling salesman problem with replenishment arcs","volume":"7","year":"2000","journal-title":"International Transactions in Operational Research"},{"issue":"3-4","key":"key2020120413490926700_ref022","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/S0020-0255(01)00083-4","article-title":"Flight graph based genetic algorithm for crew scheduling in airlines","volume":"133","year":"2001","journal-title":"Information Sciences"},{"issue":"12","key":"key2020120413490926700_ref023","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1057\/jors.1995.204","article-title":"An exchange heuristic for routeing problems with time windows","volume":"46","year":"1995","journal-title":"Journal of the Operational Research Society"},{"issue":"3","key":"key2020120413490926700_ref024","doi-asserted-by":"crossref","first-page":"1850","DOI":"10.1016\/j.ejor.2004.10.033","article-title":"A branch-and-price approach for operational aircraft maintenance routing","volume":"175","year":"2006","journal-title":"European Journal of Operational Research"},{"issue":"3","key":"key2020120413490926700_ref025","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1016\/j.ejor.2007.10.065","article-title":"Genetic algorithm based approach for the integrated airline crew-pairing and rostering problem","volume":"199","year":"2009","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"key2020120413490926700_ref026","first-page":"29","article-title":"An optimization model for aircraft maintenance scheduling and re-assignment","volume":"37","year":"2003","journal-title":"Transportation Research Part A: Policy and Practice"},{"issue":"1","key":"key2020120413490926700_ref027","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1287\/trsc.32.1.43","article-title":"The four-day aircraft maintenance routing problem","volume":"32","year":"1998","journal-title":"Transportation Science"},{"key":"key2020120413490926700_ref028","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.cie.2015.02.005","article-title":"A parallel simulated annealing method for the vehicle routing problem with simultaneous pickup-delivery and time windows","volume":"83","year":"2015","journal-title":"Computers & Industrial Engineering"},{"issue":"3","key":"key2020120413490926700_ref029","doi-asserted-by":"crossref","first-page":"6276","DOI":"10.1016\/j.eswa.2008.07.013","article-title":"Population declining ant colony optimization algorithm and its applications","volume":"36","year":"2009","journal-title":"Expert Systems with Applications"},{"issue":"2","key":"key2020120413490926700_ref030","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.tre.2010.09.010","article-title":"An ant colony optimization model: the period vehicle routing problem with time windows","volume":"47","year":"2011","journal-title":"Transportation Research Part E: Logistics and Transportation Review"},{"issue":"1","key":"key2020120413490926700_ref031","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.ejor.2013.01.043","article-title":"A new crossover approach for solving the multiple travelling salesmen problem using genetic algorithms","volume":"228","year":"2013","journal-title":"European Journal of Operational Research"},{"issue":"10","key":"key2020120413490926700_ref032","doi-asserted-by":"crossref","first-page":"2770","DOI":"10.1109\/TKDE.2015.2419659","article-title":"On the upper bounds of spread for greedy algorithms in social network influence maximization","volume":"27","year":"2015","journal-title":"IEEE Transactions on Knowledge and Data Engineering"}],"container-title":["Industrial Management &amp; Data Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IMDS-11-2016-0475\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IMDS-11-2016-0475\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:54:02Z","timestamp":1753394042000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/imds\/article\/117\/10\/2142-2170\/184662"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,4]]},"references-count":33,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2017,12,4]]}},"alternative-id":["10.1108\/IMDS-11-2016-0475"],"URL":"https:\/\/doi.org\/10.1108\/imds-11-2016-0475","relation":{},"ISSN":["0263-5577"],"issn-type":[{"value":"0263-5577","type":"print"}],"subject":[],"published":{"date-parts":[[2017,12,4]]}}}