Development of a Multimodal Microsimulation-Based Evacuation Model

2019 ◽  
Vol 2673 (10) ◽  
pp. 477-488
Author(s):  
Jahedul Alam ◽  
Muhammad Ahsanul Habib ◽  
Uday Venkatadri
Keyword(s):  
Dynamic Traffic Assignment ◽  
Route Choice ◽  
Computation Time ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Modeling Framework ◽  
Transit System ◽  
Microsimulation Modeling ◽  
Transit Route ◽  
Transit Routes

This study presents a multimodal evacuation microsimulation modeling framework. The paper first determines optimum marshal point locations and transit routes, then examines network conditions through traffic microsimulation of a mass evacuation of the Halifax Peninsula, Canada. The proposed optimization modeling approach identifies marshal point locations based on transit demand obtained from a Halifax Regional Transport network model. A mixed integer linear programming (MILP) technique is used to formulate the marshal point location and transit route choice problem. The study proposes a novel approach to solving the MILP problem, using the “branch and cut” algorithm, which demonstrates superiority in computation time and production of quality solutions. The optimization model determines 135 marshal points and 12 transit routes to evacuate approximately 8,400 transit-dependent individuals. Transit demand and marshal point locations are found to be concentrated at the core of the peninsula. The microsimulation modeling takes a dynamic traffic assignment-based approach. The simulation model predicts that it takes 22 h to evacuate all auto users but just 7 h for the transit-dependent population. The study reveals that the transit system has excess capacity to assist evacuees who switch from auto and other modes. Local traffic congestion prolongs the evacuation of a few densely-populated zones in the downtown core of the peninsula. The findings of this research help policy-makers understand the impacts of marshal point locations and transit route choice decisions on multimodal evacuation performance, and provide insights into emergency planning of multimodal evacuations under "mode switch" and transit-based evacuation scenarios.

scholarly journals Train-Scheduling Optimization Model for Railway Networks with Multiplatform Stations

2019 ◽  
Vol 12 (1) ◽  
pp. 257
Author(s):  
Gianmarco Garrisi ◽  
Cristina Cervelló-Pastor
Keyword(s):  
Mathematical Formulation ◽  
Computation Time ◽  
Mixed Integer ◽  
Initial Population ◽  
Mixed Integer Linear Program ◽  
Transit System ◽  
Train Scheduling ◽  
Railway Networks ◽  
Np Hard Problem ◽  
Problem Instances

This paper focuses on optimizing the schedule of trains on railway networks composed of busy complex stations. A mathematical formulation of this problem is provided as a Mixed Integer Linear Program (MILP). However, the creation of an optimal new timetable is an NP-hard problem; therefore, the MILP can be solved for easy cases, computation time being impractical for more complex examples. In these cases, a heuristic approach is provided that makes use of genetic algorithms to find a good solution jointly with heuristic techniques to generate an initial population. The algorithm was applied to a number of problem instances producing feasible, though not optimal, solutions in several seconds on a laptop, and compared to other proposals. Some improvements are suggested to obtain better results and further improve computation time. Rail transport is recognized as a sustainable and energy-efficient means of transport. Moreover, each freight train can take a large number of trucks off the roads, making them safer. Studies in this field can help to make railways more attractive to travelers by reducing operative cost, and increasing the number of services and their punctuality. To improve the transit system and service, it is necessary to build optimal train scheduling. There is an interest from the industry in automating the scheduling process. Fast computerized train scheduling, moreover, can be used to explore the effects of alternative draft timetables, operating policies, station layouts, and random delays or failures.

scholarly journals Investigating the Minimum Size of Study Area for an Activity-Based Travel Demand Forecasting Model

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Qiong Bao ◽  
Yongjun Shen ◽  
Lieve Creemers ◽  
Bruno Kochan ◽  
Tom Bellemans ◽  
...  
Keyword(s):  
Travel Demand ◽  
Demand Forecasting ◽  
Computation Time ◽  
Minimum Size ◽  
Modeling Framework ◽  
Travel Demand Forecasting ◽  
Geographical Unit ◽  
Microsimulation Modeling ◽  
Demand Forecasting Model

Nowadays, considerable attention has been paid to the activity-based approach for transportation planning and forecasting by both researchers and practitioners. However, one of the practical limitations of applying most of the currently available activity-based models is their computation time, especially when large amount of population and detailed geographical unit level are taken into account. In this research, we investigated the possibility of restraining the size of the study area in order to reduce the computation time when applying an activity-based model, as it is often the case that only a small territory rather than the whole region is the focus of a specific study. By introducing an accuracy level of the model, we proposed in this research an iteration approach to determine the minimum size of the study area required for a target territory. In the application, we investigated the required minimum size of the study area surrounding each of the 327 municipalities in Flanders, Belgium, with regard to two different transport modes, that is, car as driver and public transport. Afterwards, a validation analysis and a case study were conducted. All the experiments were carried out by using the FEATHERS, an activity-based microsimulation modeling framework currently implemented for the Flanders region of Belgium.

scholarly journals Metodología para creación de rutas alimentadoras en sistemas de transporte masivo

2017 ◽  
Vol 26 (45) ◽  
Author(s):  
Daniela Ospina-Toro ◽  
Eliana Mirledy Toro-Ocampo ◽  
Ramón Alfonso Gallego-Rendón
Keyword(s):  
Programming Model ◽  
Methodological Approach ◽  
Exact Algorithm ◽  
Set Partitioning ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Location Routing Problem ◽  
Transit System ◽  
Routing Problem ◽  
Location Routing

This paper proposes a methodology to identify feeder routes for areas disconnected to the Mass Transit System (MTS), in order to propose an alternative solution to the deficit in the number of passengers carried. The proposed methodology consists of two steps: (1) structuring scenarios for areas not connected to the transport system and (2) combining heuristic and exact techniques to solve the feeding routes problem considering in the restrictions the path length and passengers vehicle capacity.  To model the problem, a comparison with the Location Routing problem is established, which is usually applied to freight transport problems. The methodology proposed is a math-heuristic combining the Lin-Kernighan-Helsgaun algorithm (LKH) and the Clark and Wright’s Savings heuristic with the Branch-and-Cut exact algorithm, which is applied into a Mixed Integer Linear Programming model (MILP), also known as a Set Partitioning model (SP) for LRP. This methodological approach is validated with real instances considering locations in Pereira (Megabús), where some areas disconnected to the Central-Occidental Metropolitan Area System (AMCO) of Pereira, located in Colombia's Coffee Axis are considered.

Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

2017 ◽  
Vol 2650 (1) ◽  
pp. 74-83 ◽  
Author(s):  
Neda Masoud ◽  
Daisik Nam ◽  
Jiangbo Yu ◽  
R. Jayakrishnan
Keyword(s):  
Los Angeles ◽  
Travel Demand ◽  
Decision Support Tool ◽  
Peer To Peer ◽  
Successful Implementation ◽  
Modeling Framework ◽  
Transit System ◽  
Support Tool ◽  
Demand Shifts ◽  
Red Line

Peer-to-peer (P2P) ridesharing is a recently emerging travel alternative that can help accommodate the growth in urban travel demand and at the same time alleviate problems such as excessive vehicular emissions. Prior ridesharing projects suggest that the demand for ridesharing is usually shifted from transit, but its true benefits are realized when the demand shifts from single-occupancy vehicles. This study investigated the potential of shifting demand from private autos to transit by providing a general modeling framework that found routes for private vehicle users that were a combination of P2P ridesharing and transit. The Los Angeles Metro Red Line in California was considered for a case study because it has recently shown declining ridership trends. For successful implementation of a ridesharing system, strategically selecting locations for individuals to get on and off the rideshare vehicles is crucial, along with an appropriate pricing structure for the rides. The study conducted a parametric analysis of the application of real-time P2P ridesharing to feed the Los Angeles Metro Red Line with simulated demand. A mobile application with an innovative ride-matching algorithm was developed as a decision support tool that suggested transit-rideshare and rideshare routes.

Design of Bus Routes: Methodology and the Santo Domingo Case

2002 ◽  
Vol 1791 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Avishai Ceder ◽  
Oneximo Gonzalez ◽  
Hugo Gonzalez
Keyword(s):  
Network Design ◽  
Traffic Congestion ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Large Network ◽  
Santo Domingo ◽  
Urban Transit ◽  
Bus Network ◽  
Transit Routes

Growing traffic congestion, the importance of preserving the environment, and the problems of road safety are the main reasons to consider new initiatives worldwide in designing new urban transit routes. A need exists to develop a practical methodology for the construction of a new or improved network of bus routes along with intermodality considerations. An approach for the design of urban bus routes is presented with an example of designing new bus routes for the city of Santo Domingo in the Dominican Republic. Santo Domingo has major congestion, environmental, and safety problems. The presented approach involves a framework for the construction of operational objective functions for the bus-network-design problem. This framework takes into account passenger, operator, and community interests. The methodology combines the philosophy of mathematical programming approaches with decisionmaking techniques, so as to allow the user to select from a number of alternatives. The overall formulation is nonlinear and mixed-integer programming. The bus-network-design formulation used in the case study of Santo Domingo, a city with 3 million inhabitants, involved a large network of feasible bus routes subjected to the proposed method and resulted in 84 new bus routes. With other accompanied measures, the new bus routes will change the bus system image in Santo Domingo.

A Criterion Space Branch-and-Cut Algorithm for Mixed Integer Bilinear Maximum Multiplicative Programs

2022 ◽  
Author(s):  
Vahid Mahmoodian ◽  
Iman Dayarian ◽  
Payman Ghasemi Saghand ◽  
Yu Zhang ◽  
Hadi Charkhgard
Keyword(s):  
Objective Function ◽  
Branch And Bound ◽  
Capacity Allocation ◽  
Branch And Cut ◽  
Nash Bargaining ◽  
Mixed Integer ◽  
Bargaining Solution ◽  
Reliability Optimization ◽  
Criterion Space ◽  
Multiplicative Programs

This study introduces a branch-and-bound algorithm to solve mixed-integer bilinear maximum multiplicative programs (MIBL-MMPs). This class of optimization problems arises in many applications, such as finding a Nash bargaining solution (Nash social welfare optimization), capacity allocation markets, reliability optimization, etc. The proposed algorithm applies multiobjective optimization principles to solve MIBL-MMPs exploiting a special characteristic in these problems. That is, taking each multiplicative term in the objective function as a dummy objective function, the projection of an optimal solution of MIBL-MMPs is a nondominated point in the space of dummy objectives. Moreover, several enhancements are applied and adjusted to tighten the bounds and improve the performance of the algorithm. The performance of the algorithm is investigated by 400 randomly generated sample instances of MIBL-MMPs. The obtained result is compared against the outputs of the mixed-integer second order cone programming (SOCP) solver in CPLEX and a state-of-the-art algorithm in the literature for this problem. Our analysis on this comparison shows that the proposed algorithm outperforms the fastest existing method, that is, the SOCP solver, by a factor of 6.54 on average. Summary of Contribution: The scope of this paper is defined over a class of mixed-integer programs, the so-called mixed-integer bilinear maximum multiplicative programs (MIBL-MMPs). The importance of MIBL-MMPs is highlighted by the fact that they are encountered in applications, such as Nash bargaining, capacity allocation markets, reliability optimization, etc. The mission of the paper is to introduce a novel and effective criterion space branch-and-cut algorithm to solve MIBL-MMPs by solving a finite number of single-objective mixed-integer linear programs. Starting with an initial set of primal and dual bounds, our proposed approach explores the efficient set of the multiobjective problem counterpart of the MIBL-MMP through a criterion space–based branch-and-cut paradigm and iteratively improves the bounds using a branch-and-bound scheme. The bounds are obtained using novel operations developed based on Chebyshev distance and piecewise McCormick envelopes. An extensive computational study demonstrates the efficacy of the proposed algorithm.

A New Formulation for the Dial-a-Ride Problem

2021 ◽  
Author(s):  
Yannik Rist ◽  
Michael A. Forbes
Keyword(s):  
Time Window ◽  
Valid Inequalities ◽  
Route Planning ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Planning Problem ◽  
Current State ◽  
New Formulation ◽  
First Time ◽  
Delivery Location

This paper proposes a new mixed integer programming formulation and branch and cut (BC) algorithm to solve the dial-a-ride problem (DARP). The DARP is a route-planning problem where several vehicles must serve a set of customers, each of which has a pickup and delivery location, and includes time window and ride time constraints. We develop “restricted fragments,” which are select segments of routes that can represent any DARP route. We show how to enumerate these restricted fragments and prove results on domination between them. The formulation we propose is solved with a BC algorithm, which includes new valid inequalities specific to our restricted fragment formulation. The algorithm is benchmarked on existing and new instances, solving nine existing instances to optimality for the first time. In comparison with current state-of-the-art methods, run times are reduced between one and two orders of magnitude on large instances.

Modelling Urban Public Transit Users' Route Choice Behaviour

2011 ◽  
pp. 134-146
Author(s):  
Yulin Lee ◽  
Jonathan Bunker ◽  
Luis Ferreira
Keyword(s):  
Public Transport ◽  
Public Transit ◽  
Route Choice ◽  
User Equilibrium ◽  
Urban Transport ◽  
Transit Assignment ◽  
The Road ◽  
Transit Route ◽  
The 1960S ◽  
Assignment Models

Public transport is one of the key promoters of sustainable urban transport. To encourage and increase public transport patronage it is important to investigate the route choice behaviours of urban public transit users. This chapter reviews the main developments of modelling urban public transit users’ route choice behaviours in a historical perspective, from the 1960s to the present time. The approaches reviewed for this study include the early heuristic studies on finding the least-cost transit route and all-or-nothing transit assignment, the bus common lines problem, the disaggregate discrete choice models, the deterministic and stochastic user equilibrium transit assignment models, and the recent dynamic transit assignment models. This chapter also provides an outlook for the future directions of modelling transit users’ route choice behaviours. Through the comparison with the development of models for motorists’ route choice and traffic assignment problems, this chapter advocates that transit route choice research should draw inspiration from the research outcomes from the road area, and that the modelling practice of transit users’ route choice should further explore the behavioural complexities.

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