Journal ArticleDOI
A school bus scheduling problem
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TLDR
This paper introduces a school bus scheduling problem wherein trips for each school are given, and model the problem as a vehicle routing problem with time windows (VRPTW) by treating a trip as a virtual stop.About:
This article is published in European Journal of Operational Research.The article was published on 2012-04-16. It has received 81 citations till now. The article focuses on the topics: Generalized assignment problem & Job shop scheduling.read more
Citations
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Optimization methods for power scheduling problems in smart home: Survey
Sharif Naser Makhadmeh,Ahamad Tajudin Khader,Mohammed Azmi Al-Betar,Syibrah Naim,Ammar Kamal Abasi,Zaid Abdi Alkareem Alyasseri,Zaid Abdi Alkareem Alyasseri +6 more
TL;DR: This paper reviews the most pertinent studies on optimization methods that address power scheduling problem in a smart home (PSPSH), and a critical analysis of state-of-the-art methods are provided.
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Population-Based Incremental Learning Algorithm for a Serial Colored Traveling Salesman Problem
TL;DR: A population-based incremental learning (PBIL) approach to S-CTSP, a generalization of the well-known multiple traveling salesman problem, which shows that the augmented PBIL is effective and well outperforms the genetic algorithms and CPLEX.
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Production-inventory-routing coordination with capacity and time window constraints for perishable products: Heuristic and meta-heuristic algorithms
TL;DR: In this paper, a mathematical programming approach is taken to consider these two issues together in order to maximize the profits obtained by selling the products, and two heuristic and meta-heuristic algorithms are proposed to solve the proposed problem.
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The school bus routing and scheduling problem with transfers
TL;DR: The results show that allowing transfers reduces total operating costs significantly while average and maximum user ride times are comparable to solutions without transfers.
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Variable Neighborhood Search for a Colored Traveling Salesman Problem
TL;DR: A variable neighborhood search (VNS) approach for colored traveling salesman problem, in which city colors are diverse, i.e., each city has one to all salesmen’s colors while other elements of the problem keeps unchanged, and results show that the proposed VNS is an efficient heuristics to solve CTSP.
References
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Journal ArticleDOI
Combinatorial optimization: algorithms and complexity
TL;DR: This clearly written, mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NPcomplete problems, more.
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The school bus routing problem: A review
Junhyuk Park,Byung-In Kim +1 more
TL;DR: The various assumptions, constraints, and solution methods used in the literature on SBRP are summarized and a list of issues requiring further research is presented.
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Routing and Scheduling of School Buses by Computer
Lawrence Bodin,Lon Berman +1 more
TL;DR: A new procedure for the routing and scheduling of school buses is presented, implemented and tested successfully in two school districts and resulted in about a 20% savings in cost and the transportation of 600 additional students with one extra bus in the second.
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A computerized approach to the New York City school bus routing problem
TL;DR: This paper investigates various issues related to the development of a computerized system to help route and schedule school buses throughout the five boroughs of New York City and provides a solution requiring far fewer buses than are currently in use.
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Multi-depot vehicle scheduling problems with time windows and waiting costs
TL;DR: In this paper, the authors considered costs on exact waiting times between two consecutive tasks instead of minimal waiting times, which gave rise to a nonlinear objective function in the model and showed that such a general solution methodology outperforms specialized algorithms when minimal waiting costs are used.