scholarly journals Optimal Design of Transportation Networks with Automated Vehicle Links and Congestion Pricing

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yipeng Ye ◽  
Hua Wang
Keyword(s):  
Network Design ◽  
Traffic Congestion ◽  
Solution Method ◽  
Congestion Pricing ◽  
Market Penetration ◽  
Travel Costs ◽  
Automated Vehicle ◽  
Proposed Model ◽  
Total Travel Time ◽  
Upper Level

We propose a bi-level network design model comprising automated vehicle (AV) links and congestion pricing to improve traffic congestion. As upper-level road planners strive to minimize total travel-time costs by optimizing both the network design and the congestion pricing, lower-level travelers make choices about their routes to minimize their individual travel costs. Our proposed model integrates a network design and congestion pricing to improve traffic congestion and we use a relaxation-based method to solve the model. We conducted a series of numerical tests to analyze the proposed model and solution method. Our results indicate that network design is more effective than congestion pricing when the AV market penetration is high and the opposite is true when AV penetration is low. More importantly, we find that a network design of automated vehicle links with congestion pricing is superior to a single network design or congestion pricing, especially when both AVs and conventional vehicles have a relatively large market penetration.

scholarly journals Topological Effects and Performance Optimization in Transportation Continuous Network Design

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianjun Wu ◽  
Xin Guo ◽  
Huijun Sun ◽  
Bo Wang
Keyword(s):  
Network Design ◽  
Performance Optimization ◽  
Transportation Network ◽  
Small World ◽  
User Equilibrium ◽  
Solution Approach ◽  
Proposed Model ◽  
Upper Level ◽  
And Performance ◽  
Bilevel Transportation

Because of the limitation of budget, in the planning of road works, increased efforts should be made on links that are more critical to the whole traffic system. Therefore, it would be helpful to model and evaluate the vulnerability and reliability of the transportation network when the network design is processing. This paper proposes a bilevel transportation network design model, in which the upper level is to minimize the performance of the network under the given budgets, while the lower level is a typical user equilibrium assignment problem. A new solution approach based on particle swarm optimization (PSO) method is presented. The topological effects on the performance of transportation networks are studied with the consideration of three typical networks, regular lattice, random graph, and small-world network. Numerical examples and simulations are presented to demonstrate the proposed model.

Data-Driven Stochastic Optimization for Transportation Road Network Design Under Uncertainty

2020 ◽  
pp. 231-278
Author(s):  
Suh-Wen Chiou
Keyword(s):  
Stochastic Optimization ◽  
Network Design ◽  
Travel Cost ◽  
Data Driven ◽  
Bundle Method ◽  
Risk Exposure ◽  
Travel Costs ◽  
Trade Offs ◽  
Proposed Model ◽  
Hazmat Transportation

A data-driven stochastic program for bi-level network design with hazardous material (hazmat) transportation is proposed in this chapter. In order to regulate the risk associated with hazmat transportation and minimize total travel cost on interested area under stochasticity, a multi-objective stochastic optimization model is presented to determine generalized travel cost for hazmat carriers. Since the bi-level program is generally non-convex, a data-driven bundle method is presented to stabilize solutions of the proposed model and reduce relative gaps between iterations. Numerical comparisons are made with existing risk-averse models. The results indicate that the proposed data-driven stochastic model becomes more resilient than others in minimizing total travel cost and mitigating risk exposure. Moreover, the trade-offs among maximum risk exposure, generalized travel costs, and maximum equitable risk spreading over links are empirically investigated in this chapter.

scholarly journals Joint Implementation of Signal Control and Congestion Pricing in Transportation Network

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Mao ◽  
Feifei Qin ◽  
Yihong Hu ◽  
Zhijia Tan
Keyword(s):  
Transportation Network ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Joint Implementation ◽  
Simultaneous Optimization ◽  
Signal Control ◽  
Solution Methods ◽  
Total Travel Time ◽  
Upper Level ◽  
Bilevel Programs

The policy of jointly implementing signal control and congestion pricing in the transportation network is investigated. Bilevel programs are developed to model the simultaneous optimization of signal setting and congestion toll. The upper level aims to maximize the network reserve capacity or minimize the total travel time, subject to signal setting and toll constraints. The lower level is a deterministic user equilibrium problem given a plan of signal setting and congestion charge. Then the bilevel programs are transferred into the equivalent single level programs, and the solution methods are discussed. Finally, a numerical example is presented to illustrate the concepts and methods, and it is shown that the joint implementation policy can achieve promising results.

Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

2021 ◽  
pp. 0734242X2110039
Author(s):  
Elham Shadkam
Keyword(s):  
Waste Management ◽  
Network Design ◽  
Optimization Algorithm ◽  
Reverse Logistics ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Fixed Costs ◽  
Logistics System ◽  
Cuckoo Optimization Algorithm ◽  
Proposed Model

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

Traffic Congestion Reduction and Accident Circumvention System via Incorporation of CAV and VANET

2021 ◽  
Vol 12 (1) ◽  
pp. 53-72
Author(s):  
Mohsin Khan ◽  
Bhavna Arora
Keyword(s):  
Real Time ◽  
Data Transmission ◽  
Traffic Congestion ◽  
Ad Hoc Network ◽  
Discrete System ◽  
Ad Hoc ◽  
New Age ◽  
The Real ◽  
Automated Vehicle ◽  
The Core

Connected automated vehicle (CAV) technology is the core for the new age vehicles in research phase to communicate with one another and assimilation of vehicular ad-hoc network (VANET) for the transference of data between vehicles at a quantified place and time. This manuscript is an enactment of the algorithms associated to the maintenance of secure distance amongst vehicles, lane shifting, and overtaking, which will diminish the occurrence of collisions and congestions especially phantom jams. Those implementations are centered over CAV and VANET technology for the interconnection of the vehicles and the data transmission. The data is associated to the aspects of a vehicle such as speed, position, acceleration, and acknowledgements, which acts as the fundamentals for the computation of variables. In accordance with the environment of a particular vehicle (i.e., its surrounding vehicles), real-time decisions are taken based on the real-time computation of the variables in a discrete system.

Designing an uncertain bi-objective green leagile capacitated lot sizing problem considering FM/M/C queue system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Masoud Rabbani ◽  
Soroush Aghamohamadi Bosjin ◽  
Neda Manavizadeh ◽  
Hamed Farrokhi-Asl
Keyword(s):  
Mathematical Model ◽  
Solution Method ◽  
Lot Sizing ◽  
Test Problems ◽  
Content Type ◽  
Queue System ◽  
Proposed Model ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing ◽  
To Receive

Purpose This paper aims to present a novel bi-objective mathematical model for a production-inventory system under uncertainty. Design/methodology/approach This paper addresses agile and lean manufacturing concepts alongside with green production methods to design an integrated capacitated lot sizing problem (CLSP). From a methodological perspective, the problem is solved in three phases. In the first step, an FM/M/C queuing system is used to minimize the number of customers waited to receive their orders. In the second step, an effective approach is applied to deal with the fuzzy bi-objective model and finally, a hybrid metaheuristic algorithm is used to solve the problem. Findings Some numerical test problems and sensitivity analyzes are conducted to measure the efficiency of the proposed model and the solution method. The results validate the model and the performance of the solution method compared to Gams results in small size test problems and prove the superiority of the hybrid algorithm in comparison with the other well-known metaheuristic algorithms in large size test problems. Originality/value This paper presents a novel bi-objective mathematical model for a CLSP under uncertainty. The proposed model is conducted on a practical case and several sensitivity analysis are conducted to assess the behavior of the model. Using a queue system, this problem aims to reduce the items waited in the queue to receive service. Two objective functions are considered to maximize the profit and minimize the negative environmental effects. In this regard, the second objective function aims to reduce the amount of emitted carbon.

scholarly journals The Effect of Congestion Pricing Scheme on the Generalized Cost and Speed of a Motorcycle

2016 ◽  
Vol 15 (1) ◽  
pp. 95-106
Author(s):  
Gito SUGIYANTO
Keyword(s):  
Traffic Congestion ◽  
Demand Management ◽  
Congestion Pricing ◽  
Flow Speed ◽  
Free Flow ◽  
Vehicle Speed ◽  
Traffic Jams ◽  
Pricing Scheme ◽  
Free Flow Speed ◽  
Generalized Cost

Traffic congestion is one of the significant transport problems in many cities in developing countries. Increased economic growth and motorization have created more traffic congestion. The application of transportation demand management like congestion pricing can reduce congestion, pollution and increase road safety. The aim of this research is to estimate the congestion pricing of motorcycles and the effect of a congestion pricing scheme on the generalized cost and speed of a motorcycle. The amount of congestion pricing is the difference between actual generalized cost in traffic jams and in free-flow speed conditions. The analysis approach using 3 components of generalized costs of motorcycle: vehicle operating, travel time and externality cost (pollution cost). The approach to analyze the pollution cost is marginal-health cost and fuel consumption in traffic jams and free-flow speed conditions. The value of time based on Gross Regional Domestic Product per capita in Yogyakarta City in October 2012. The simulation to estimate the effect of congestion pricing using Equilibre Multimodal, Multimodal Equilibrium-2 (EMME-2) software. The results of this study show that while the free-flow speed of a motorcycle to the city of Yogyakarta is 42.42 km/h, with corresponding generalized cost of IDR1098 per trip, the actual speed in traffic jams is 10.77 km/h producing a generalized cost of IDR2767 per trip, giving a congestion pricing for a motorcycle of IDR1669 per trip. Based on the simulation by using EMME-2, the effect of congestion pricing will increase on vehicle speed by 0.72 to 8.11 %. The highest increase of vehicle speed occurred in Malioboro Street at 2.26 km/h, while the largest decrease occurred in Mayor Suryotomo Street at north-south direction at 1.07 km/h. Another effect of this application for motorcycles users will decrease the generalized cost by 1.09 to 6.63 %.

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.

scholarly journals Timetable Design for Urban Rail Line with Capacity Constraints

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Ting Zhu ◽  
Bao-Hua Mao ◽  
Lu Liu ◽  
Ming-Gao Li
Keyword(s):  
Solution Method ◽  
Operating Cost ◽  
Capacity Constraints ◽  
Scheduling Model ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line ◽  
First Come First Serve ◽  
Waiting Cost ◽  
Simulation Results

To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.

scholarly journals Network Design for Municipal Solid Waste Collection: A Case Study of the Nanjing Jiangbei New Area

2018 ◽  
Vol 15 (12) ◽  
pp. 2812 ◽  
Author(s):  
Jing Liang ◽  
Ming Liu
Keyword(s):  
Municipal Solid Waste ◽  
Network Design ◽  
Solid Waste ◽  
Relative Size ◽  
Service Level ◽  
Optimal Number ◽  
Mixed Integer ◽  
Proposed Model ◽  
The Impact ◽  
Operation Cost

Garbage collection is an important part of municipal engineering. An effective service network design can help to reduce the municipal operation cost and improve its service level. In this paper, we propose an optimization model for the network design of municipal solid waste (MSW) collection in the Nanjing Jiangbei new area. The problem was formulated as a mixed integer nonlinear programming (MINLP) model with an emphasis on minimizing the annual operation cost. The model simultaneously decides on the optimal number of refuse transfer stations (RTSs), determines the relative size and location for each RTS, allocates each community to a specific RTS, and finally identifies the annual operation cost and service level for the optimal scenario as well as other scenarios. A custom solution procedure which hybrids an enumeration rule and a genetic algorithm was designed to solve the proposed model. A sensitivity analysis was also conducted to illustrate the impact of changes in parameters on the optimality of the proposed model. Test results revealed that our model could provide tangible policy recommendations for managing the MSW collection.

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