fa Iterated Local Search Algorithm with Strategic Oscillation for School Bus Routing Problem with Bus Stop Selection Research Paper مقاله پژوهشی The school bus routing problem (SBRP) represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm) and I-ILS (a variant of Insertion with Iterated Local Search algorithm) are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBRP The school bus routing problem (SBRP) represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm) and I-ILS (a variant of Insertion with Iterated Local Search algorithm) are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBRP School Bus Routing Problem , Combinatorial Optimization , Iterated Local Search Algorithm , Strategic Oscillation , School Bus Routing Problem , Combinatorial Optimization , Iterated Local Search Algorithm , Strategic Oscillation , 0 0 http://system.khu.ac.ir/ijsom/browse.php?a_code=A-10-801-1&slc_lang=fa&sid=1 Mohammad Saied Fallah Niasar Mohammad Saied Fallah Niasar fallah.pasco@gmail.com 100319475328460078 100319475328460078 Yes Department of Engineering Management, Faculty of Applied Economics, University of Antwerp, Belgium Department of Engineering Management, Faculty of Applied Economics, University of Antwerp, Belgium Luca Talarico Luca Talarico luca.talarico@uantwerpen.be 100319475328460079 100319475328460079 No Department of Engineering Management, Faculty of Applied Economics, University Antwerp, Belgium Department of Engineering Management, Faculty of Applied Economics, University Antwerp, Belgium Mehdi Sajadifar Mehdi Sajadifar mehdi.sajadifar@gmail.com 100319475328460080 100319475328460080 No Department of Industrial Engineering, University of Science and Culture, Tehran, Iran Department of Industrial Engineering, University of Science and Culture, Tehran, Iran Amir Hosein Tayebi Amir Hosein Tayebi amirhossein.tayebi@student.uantwerpen.be 100319475328460081 100319475328460081 No Department of Engineering Management, Faculty of Applied Economics, University Antwerp, Belgium Department of Engineering Management, Faculty of Applied Economics, University Antwerp, Belgium