Service Optimization for Bus Corridors with Group Bus Strategy
22 Sep 2018-pp 80-85
TL;DR: The proposed method is efficient for overloaded bus and waiting time saving, and the optimized bus service significantly reduces total cost and improves service level.
Abstract: To improve passengers' comfort level and decrease waiting time consumption at peak hour in operation of urban public transit. A model is presented, and objective function is waiting time cost and operator cost which is minimized by the optimized headway and dispatch sequence, subjected to the constraints of operable buses and buses required for passengers who are not on board. The sum of the number of people in the bus and the number of people waiting for boarding at the stop is relative to the full load rate of the passenger capacity. It is greater than the maximum number of passengers under critical full load rate, the integrating strategy can be applied in passengers with multi-service demand. Comparing with the actual word, optimized result S2 and S3 effectively alleviate passenger' crowding in the bus and provide a more relaxed environment for passengers. The proposed method is efficient for overloaded bus and waiting time saving, and the optimized bus service significantly reduces total cost and improves service level.
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04 Jun 2007
TL;DR: In this paper, the authors present an introduction to transit service planning, Data Requirements and Collection Frequency and Headway Determination, Timetable Development, Advanced Timetables I: Maximum Passenger Load, AdvancedTimetables II: Maximum Synchronization, Vehicle Scheduling I: Fixed Schedules, Vehicle Schedule II: Variable Schedules.
Abstract: Preface, Introduction to Transit Service Planning, Data Requirements and Collection Frequency and Headway Determination, Timetable Development, Advanced Timetables I: Maximum Passenger Load, Advanced Timetables II: Maximum Synchronization, Vehicle Scheduling I: Fixed Schedules, Vehicle Scheduling II: Variable Schedules, Vehicle-type and Size Considerations in Vehicle Scheduling, Scheduling, Passenger Demand, Route Choice and Assignment, Service Design and Connectivity, Network (Routes) Design, Designing Short-turn trips, Smart Shuttle and Feeder Service, Service Reliability and control, Future Developments in Transit Operations, Answers to Exercises, Index
444 citations
TL;DR: In this paper, a genetic algorithm incorporating Monte Carlo simulation is proposed to solve the problem of deadheading in a special case of the stop-skipping problem, allowing a bus vehicle to skip stops between the dispatching terminal point and a designated stop.
Abstract: When a bus is late and behind schedule, the stop-skipping scheme allows the bus vehicle to skip one or more stops to reduce its travel time. The deadheading problem is a special case of the stop-skipping problem, allowing a bus vehicle to skip stops between the dispatching terminal point and a designated stop. At the planning level, the optimal operating plans for these two schemes should be tackled for the benefits of bus operator as well as passengers. This paper aims to propose a methodology for this objective. Thus, three objectives are first proposed to reflect the benefits of bus operator and/or passengers, including minimizing the total waiting time, total in-vehicle travel time and total operating cost. Then, assuming random bus travel time, the stop-skipping is formulated as an optimization model minimizing the weighted sum of the three objectives. The deadheading problem can be formulated via the same minimization model further adding several new constraints. Then, a Genetic Algorithm Incorporating Monte Carlo Simulation is proposed to solve the optimization model. As validated by a numerical example, the proposed algorithm can obtain a satisfactory solution close to the global optimum.
251 citations
"Service Optimization for Bus Corrid..." refers background in this paper
...INTRODUCTION Transit system, especially the urban bus system, is of considerable significance for the sustainable development of transport systems and also the robust operation of the entire society [1]....
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TL;DR: In this paper, the authors propose an optimization model to determine a limited-stop service route to be operated in parallel with the local service and its associated frequency to maximize total user welfare.
Abstract: Long in-vehicle travel times resulting from frequent stops make bus service an unattractive choice for many commuters. Limited-stop bus services however have the advantage of shorter in-vehicle times experienced by passengers. In this work, we seek to modify a given bus service by optimally reassigning some number of bus trips, as opposed to providing additional trips, to operate a limited-stop service. We propose an optimization model to determine a limited-stop service route to be operated in parallel with the local service and its associated frequency to maximize total user welfare. A few theoretical properties of the model are established and used to develop a solution approach. As a proof of concept, we present numerical results obtained using real-world data together with comprehensive discussions of solution quality, computational times and the model’s sensitivity to different parameters. Finally, we solve the optimization model for 178 real-world bus routes with different characteristics in order to demonstrate the impacts of some key attributes on potential benefits of limited-stop services.
56 citations
TL;DR: In this article, the authors proposed a hybrid approach, which combines analytic optimization with a genetic algorithm to solve multi-dimensional nonlinear mixed integer optimization problems for a bus transit system connecting a major terminal to local regions.
Abstract: Conventional bus service (with fixed routes and schedules) has lower average cost than flexible bus service (with demand-responsive routes) at high demand densities. At low demand densities flexible bus service has lower average costs and provides convenient door-to-door service. Bus size and operation type are related since larger buses have lower average cost per passenger at higher demand densities. The operation type and other decisions are jointly optimized here for a bus transit system connecting a major terminal to local regions. Conventional and flexible bus sizes, conventional bus route spacings, areas of service zones for flexible buses, headways, and fleet sizes are jointly optimized in multi-dimensional nonlinear mixed integer optimization problems. To solve them, we propose a hybrid approach, which combines analytic optimization with a Genetic Algorithm. Numerical analysis confirms that the proposed method provides near-optimal solutions and shows how the proposed Mixed Fleet Variable Type Bus Operation (MFV) can reduce total cost compared to alternative operations such as Single Fleet Conventional Bus (SFC), Single Fleet Flexible Bus (SFF), Mixed Fleet Conventional Bus (MFC) and Mixed Fleet Flexible Bus (MFF). With consistent system-wide bus sizes, capital costs are reduced by sharing fleets over times and over regions. The sensitivity of results to several important parameters is also explored.
55 citations
"Service Optimization for Bus Corrid..." refers methods in this paper
...To minimize these costs, a model with a genetic algorithm can determine frequencies and the proper stations which can be skipped, as well as where turning back can occur, given an origindestination trip matrix[9]....
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01 Jul 2013
TL;DR: This work proposes an optimization model to determine a limited-stop service route to be operated in parallel with the local service and its associated frequency to maximize total user welfare.
Abstract: Singapore-MIT Alliance for Research and Technology (SMART) (Future Urban Mobility research program)
51 citations
"Service Optimization for Bus Corrid..." refers background in this paper
...He proposed an optimization model to determine a limited-stop service route to be operated in parallel with the local service and its associated frequency to maximize total user welfare [6]....
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