Solving School Bus Routing Problem with genetic algorithm

Sghaier, Sayda Ben; Guedria, Najeh Ben; Mraïhi, Rafaa

doi:10.1109/icadlt.2013.6568426

Cited by 16 publications

(8 citation statements)

References 13 publications

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“…The experimental results showed that applying ACO at first, plays an important role in generating efficient solutions. Sghaier et al (2013) used the Genetic approach to solve the (SBRP) with the introduction of new genetic operators for the purpose of enhancing the performance of the genetic algorithm. The objectives include minimizing the cost of the transportation by cutting down the overall traveled distance and the amount of bus operations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The SBRP is in the class of NP-hard problems, meaning that no polynomial time algorithm has been found yet to resolve the problem. Many efforts have been made to find a solution to the SBRP using approaches such as genetic algorithm (Sghaier et al, 2013), Harmony search (Geem et al, 2005), Scatter search (Russell and Chiang, 2006) and ant colony optimization (Arias-Rojas et al, 2012). This study adopts the Intelligent Water Drops (IWD) algorithm to deal with SBRP.…”

Section: Introductionmentioning

confidence: 99%

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Solving School Bus Routing Problem by Intelligent Water Drops Algorithm

Jaradat

Shatnawi

2020

Journal of Computer Science

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The School Bus Routing Problem (SBRP) is an essential subject in the development of transportation. Solving the problem will have a great impact on the transportation systems by improving the quality of the provided service and reducing the operations costs. SBRP tries to find an efficient school buses plan where each bus takes up students from different bus stops and transports them to their schools while fulfilling number constraints including the maximum bus capacity and the time window of a school. This study used Intelligent Water Drops (IWD) optimization approach to resolve (SBRP). IWD is a meta-heuristic swarmbased optimization technique that simulates natural water drops. The scheme of the IWD algorithm is applied here to find a reasonable solution to SBRP. The application of IWD algorithm produces satisfying results within a reasonable amount of time.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Solving School Bus Routing Problem by Intelligent Water Drops Algorithm

Jaradat

Shatnawi

2020

Journal of Computer Science

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“…), meta-heuristic techniques produces optimal or near optimal solution in a reasonable amount of computational time. Genetic algorithm has been widely used to solve several combinatorial optimization problems, among which is the school bus routing problem [17], optimal allocation of project supervisors to students [30], optimal allocation of devices to control power line flows [32]. It is used for determining the best solution out of many possible solutions.…”

Section: Genetic Algorithmmentioning

confidence: 99%

“…Various approaches had been used to solve bus route generation problem. Such problems are usually solved by exact methods [7][8][9][10] or meta-heuristics which include ant colony optimization (ACO) [11,12], time savings heuristic and sweep method [13], tabu search [14,15] and genetic algorithm (GA) [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Solving School Bus Routing Problem using Genetic Algorithm-based Model

Oluwadare¹,

Oguntuyi²,

Nwaiwu³

2018

IJISA

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School Bus Routing Problem is an optimization problem which falls under the class of the Vehicle Routing Problem. It involves the use of a fleet of vehicles to efficiently and optimally transport students to and from their schools. To solve this problem, optimal school bus routes are found by minimizing the number of buses, the number of routes and the total distance traversed along all routes. Manual routing of school buses have led to creation of many routes, increased number of buses and several buses navigating the same route, thereby incurring more cost. One of such methods used in solving school bus routing problems is meta-heuristic method which has proven better results in terms of optimal solution and reduced time complexity. In this study, Genetic algorithm is utilized to solve the school bus routing problem because of its simplicity and ability to generate many possible solutions. The algorithm is implemented in C# programming language and tested using secondary data obtained from Ondo State Free-School Bus Shuttle Scheme, Akure, Nigeria. The result shows that of all four nodes (bus stops) used in performance evaluation, Alakure to Oke-Aro junction bus stop presents as the best route which covers a total of 69 nodes with a total distance of 34.5km. This shows that there can be less number of buses in use and reduced number of routes in which the buses are assigned.

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“…The problem is widely studied and a review of papers on SPRP solutions is presented by Park and Kim (2010). The work on solving the problem has continued by the adaptation of various methods such as the branch-and-cut algorithm (Riera-Ledesma and Salazar-González, 2012), ant colony optimization (Addor et al, 2013;Arias-Rojas et al, 2012;Bronshtein and Vagapova, 2015;Yigit and Unsal, 2016), simulated annealing (Manumbu et al, 2014), the genetic algorithm (Sghaier et al, 2013), tabu search (Pacheco et al, 2013), the GRASP (greedy randomized adaptative search procedure) metaheuristic (Siqueira et al, 2016), the time saving heuristic (Worwa, 2014), the harmony search heuristic (Kim and Park, 2013), or the column-generation-based algorithm (Caceres et al, 2014). In the work of Chen et al (2015) two algorithms for solving the SBRP are proposed: an exact method of mixed integer programming (MIP) and hybrid simulated annealing with the local search metaheuristic.…”

Section: Introductionmentioning

confidence: 99%

A Relation of Dominance for the Bicriterion Bus Routing Problem

Widuch

2017

International Journal of Applied Mathematics and Computer Science

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A bicriterion bus routing (BBR) problem is described and analysed. The objective is to find a route from the start stop to the final stop minimizing the time and the cost of travel simultaneously. Additionally, the time of starting travel at the start stop is given. The BBR problem can be resolved using methods of graph theory. It comes down to resolving a bicriterion shortest path (BSP) problem in a multigraph with variable weights. In the paper, differences between the problem with constant weights and that with variable weights are described and analysed, with particular emphasis on properties satisfied only for the problem with variable weights and the description of the influence of dominated partial solutions on non-dominated final solutions. This paper proposes methods of estimation a dominated partial solution for the possibility of obtaining a non-dominated final solution from it. An algorithm for solving the BBR problem implementing these estimation methods is proposed and the results of experimental tests are presented.

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Solving School Bus Routing Problem with genetic algorithm

Cited by 16 publications

References 13 publications

Solving School Bus Routing Problem by Intelligent Water Drops Algorithm

Solving School Bus Routing Problem by Intelligent Water Drops Algorithm

Solving School Bus Routing Problem using Genetic Algorithm-based Model

A Relation of Dominance for the Bicriterion Bus Routing Problem

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