000151059 001__ 151059 000151059 005__ 20250221105703.0 000151059 0247_ $$2doi$$a10.3390/math10091390 000151059 0248_ $$2sideral$$a129163 000151059 037__ $$aART-2022-129163 000151059 041__ $$aeng 000151059 100__ $$0(orcid)0000-0001-7603-9380$$aCalvete, Herminia I.$$uUniversidad de Zaragoza 000151059 245__ $$aApproaching the Pareto Front in a Biobjective Bus Route Design Problem Dealing with Routing Cost and Individuals’ Walking Distance by Using a Novel Evolutionary Algorithm 000151059 260__ $$c2022 000151059 5060_ $$aAccess copy available to the general public$$fUnrestricted 000151059 5203_ $$aThis paper addresses a biobjective bus routing problem that pays attention to both the routing cost and the total distance walked by the individuals to reach their assigned pickup point. These two objectives are conflicting. Generally, the less the individuals walk, the more the number of visited pickup points and so the more the routing cost. In addition, the problem deals with finding the set of pickup points visited among the set of potential locations, identifying the set of individuals assigned to each visited pickup point, and designing the bus routes. Taking into account the highly combinatorial nature of the problem, an evolutionary algorithm is proposed to approach the associated Pareto front. Its main novelties are twofold. The first is the way in which the chromosomes are encoded since they only provide information about the number of routes and the visited pickup points. The second novelty lies in the procedure to construct a feasible solution from the chromosome, which involves a heuristic and several local search procedures to improve both objective functions. Computational experiments are carried out to check the performance of the algorithm in terms of the quality of the Pareto front yielded. 000151059 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E41-20R$$9info:eu-repo/grantAgreement/ES/MCIU/PID2019-104263RB-C43 000151059 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000151059 590__ $$a2.4$$b2022 000151059 591__ $$aMATHEMATICS$$b23 / 329 = 0.07$$c2022$$dQ1$$eT1 000151059 592__ $$a0.446$$b2022 000151059 593__ $$aComputer Science (miscellaneous)$$c2022$$dQ2 000151059 593__ $$aMathematics (miscellaneous)$$c2022$$dQ2 000151059 593__ $$aEngineering (miscellaneous)$$c2022$$dQ2 000151059 594__ $$a3.5$$b2022 000151059 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000151059 700__ $$0(orcid)0000-0002-5630-3719$$aGalé, Carmen$$uUniversidad de Zaragoza 000151059 700__ $$0(orcid)0000-0001-9993-9816$$aIranzo, José A.$$uUniversidad de Zaragoza 000151059 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera. 000151059 773__ $$g10, 9 (2022), 1390 [17 pp.]$$pMathematics (Basel)$$tMathematics$$x2227-7390 000151059 8564_ $$s952911$$uhttps://zaguan.unizar.es/record/151059/files/texto_completo.pdf$$yVersión publicada 000151059 8564_ $$s2738417$$uhttps://zaguan.unizar.es/record/151059/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000151059 909CO $$ooai:zaguan.unizar.es:151059$$particulos$$pdriver 000151059 951__ $$a2025-02-21-09:53:31 000151059 980__ $$aARTICLE