An Improved ILP System for Driver Scheduling

Fores, Sarah; Proll, L. G.; Wren, Anthony

doi:10.1007/978-3-642-85970-0_3

Cited by 25 publications

(20 citation statements)

References 11 publications

(12 reference statements)

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“…Entre estas técnicas se destacam o Branch-and-Bound (Fores et al, 1999, Smith e Wren, 1988), o Branch-and-Price (Desrochers e Soumis, 1989, Barnhart et al, 1998) e o Branch-and-Cut (Friberg e Haase, 1999. Por outro lado, diversas metaheurísticas foram implementadas para resolver problemas de grande porte.…”

Section: Métodos De Resolução Do Pptunclassified

O uso da metaheurística Guided Local Search para resolver o problema de escala de motoristas de ônibus urbano

Silva¹,

Silva

2015

TRANSPORTES

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Resumo: Neste artigo é aplicada a metaheurística Guided Local Search (GLS) para resolver o Problema de Programação de Tripulações de Ônibus Urbano (PPT). O PPT consiste em encontrar um conjunto de jornadas a serem designadas aos motoristas que realizarão a operação diária com o menor custo. A GLS tem como princípio penalizar características indesejáveis presentes na solução corrente, com o objetivo de escapar de soluções ótimas locais. Como heurística de busca local, foi utilizada a heurística Variable Neighborhood Descent, que explora diferentes estruturas de vizinhança para encontrar um mínimo local. De acordo com pesquisa realizada pelos autores, esta abordagem é inédita para resolver o PPT. A implementação proposta foi testada com dados de problemas reais de uma empresa que opera em uma região metropolitana de Belo Horizonte. Os resultados obtidos são similares àqueles presentes na literatura, havendo possibilidades de melhorias, visto que a GLS pode ser explorada em diferentes aspectos.Palavras-chave: Guided Local Search, Programação de Tripulações do Sistema de Transporte. Metaheurística. Abstract:In this paper the metaheuristic Guided Local Search (GLS) is applied to solve the Crew Scheduling Problem (CSP) for public mass transport system. The CSP consists on finding a set of duties to be assigned to drivers in order that the daily service requirement be met at minimum cost. The GLS metaheuristic follows the basic principle of penalizing undesired characteristics that are present in the current solution and to append this penalization in the objective function with the aim of guiding the local search away from local minimum. As local search heuristic, it was employed Variable Neighborhood Descent technique, which explores different neighborhood structures to find a local optimum. According to a research conducted by the authors, this is a novel approach to solve the CSP. The proposed implementation was tested with data from real problems of a bus company operating in a metropolitan region of Belo Horizonte. The results are comparable with those reported in the literature, being subject to improvement, once the GLS can be exploited in different ways.Keywords: Guided Local Search, Crew Scheduling Problem in mass transit, Metaheuristic. INTRODUÇÃOEm muitas cidades o ônibus é o principal, senão o único meio de transporte público de passageiros. Portanto, é necessário que as empresas do ramo tenham suas atividades muito bem planejadas para atender à demanda dos usuários do sistema de maneira econômica. Para tanto, devem ser utilizadas ferramentas computacionais que auxiliam o processo de decisão. Neste contexto é que se inserem os mé-todos de otimização, os quais podem levar à redução dos custos destas empresas. Entre os custos de maiores pesos se destacam os custos operacionais com os veículos e os seus motoristas e cobradores (Bouzada, 2003) Geralmente, o planejamento de um sistema de transporte público é decomposto em etapas a fim de tornar o problema tratável do ponto de vista computacional. A etapa inicia...

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Section: Métodos De Resolução Do Pptunclassified

O uso da metaheurística Guided Local Search para resolver o problema de escala de motoristas de ônibus urbano

Silva¹,

Silva

2015

TRANSPORTES

View full text Add to dashboard Cite

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“…For problems which have a small generated set of shifts (currently fewer than 30,000) a dual approach, described by Willers et al [12] is used. If the shift set is larger, then a primal SPRINT-like [16] technique described by Fores et al [14] is employed, which ensures that all relevant generated shifts are considered when forming the optimal LP, but not all are stored internally. Both primal and dual methods are accelerated by providing an initial solution.…”

Section: Selection Of a Subset Of Shiftsmentioning

confidence: 99%

“…Most of the theoretical aspects of the TRACS II system have been presented elsewhere [2,9,10,11,12,13,14,15]. The purposes of this paper are to show how theory and practice have been brought together in a user-friendly and adaptable system providing maximum flexibility.…”

Section: Introductionmentioning

confidence: 99%

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Wren

Fores

Kwan

et al. 2003

Journal of Scheduling

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SUMMARYA substantial part of the operating costs of public transport is attributable to drivers, whose efficient use therefore is important. The compilation of optimal work packages is difficult, being NP-hard. In practice, algorithmic advances and enhanced computing power have led to significant progress in achieving better schedules. However, differences in labour practices among modes of transport and operating companies make production of a truly general system with acceptable performance a difficult proposition. TRACS II has overcome these difficulties, being used with success by a substantial number of bus and train operators. Many theoretical aspects of the system have been published previously. This paper shows for the first time how theory and practice have been brought together, explaining the many features which have been added to the algorithmic kernel to provide a user-friendly and adaptable system designed to provide maximum flexibility in practice. We discuss the extent to which users have been involved in system development, leading to many practical successes, and we summarise some recent achievements.

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“…Generate‐and‐select group : he basic steps of the generate‐and‐select method are as follows first, generate a set of valid duties according to the duty constraint; then, use a method such as a genetic algorithm , integer linear programming method , or fuzzy evaluation to screen out a set of duties satisfying the constraints of the schedule. The duty‐generation stage is independent of the duty‐selection stage.…”

Section: Introductionmentioning

confidence: 99%

A case study of Beijing bus crew scheduling: a variable neighborhood‐based approach

Ceder

Yang

et al. 2015

J of Advced Transportation

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SUMMARYCrew scheduling for bus drivers in large bus agencies is known to be a time-consuming and cumbersome problem in transit operations planning. This paper investigates a new meta-heuristics approach for solving real-world bus-driver scheduling problems. The drivers' work is represented as a series of successive pieces of work with time windows, and a variable neighborhood search (VNS) algorithm is employed to solve the problem of driver scheduling. Examination of the modeling procedure developed is performed by a case study of two depots of the Beijing Public Transport Group, one of the largest transit companies in the world. The results show that a VNS-based algorithm can reduce total driver costs by up to 18.1%, implying that the VNS algorithm may be regarded as a good optimization technique to solve the bus-driver scheduling problem.

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An Improved ILP System for Driver Scheduling

Cited by 25 publications

References 11 publications

O uso da metaheurística Guided Local Search para resolver o problema de escala de motoristas de ônibus urbano

O uso da metaheurística Guided Local Search para resolver o problema de escala de motoristas de ônibus urbano

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A case study of Beijing bus crew scheduling: a variable neighborhood‐based approach

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