فهرست مطالب

Transportation Engineering - Volume:5 Issue: 3, Winter 2018

International Journal of Transportation Engineering
Volume:5 Issue: 3, Winter 2018

  • تاریخ انتشار: 1396/06/28
  • تعداد عناوین: 6
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  • Mona Issabakhsh, Seyyed-Mahdi Hosseini-Motlagh*, Mir-Saman Pishvaee, Mojtaba Saghafi Nia Pages 211-228
    Compared to center-based hemodialysis (HD), peritoneal dialysis (PD) has many advantages among which cost effectiveness and comfort of patients are the most important ones. On the other hand the number of PD patients is so small and even decreasing worldwide due to difficulties of this mode of dialysis. Therefore to encourage dialysis patients to choose PD, health system must provide a proper set of care services proportional to special needs of these patients.Applying operations research (OR) as an efficient mathematical tool and considering the realistic assumptions such as travel time uncertainty, first a Vehicle Routing Problem model is presented to serve PD patients at home with special logistic services. Thereafter, based on the criticality of timeliness in providing healthcare service, a conservative method called robust optimization, is applied to handle time uncertainty. The corresponding results show that the proposed method at the maximum uncertainty level has less than 30% variations in results and in comparison with the deterministic model increases the costs only by 1.2%.With small variations in results,this model can handle the travel time uncertainty properly and is highly appropriate and practical to be used in a sensitive application like healthcare where timeliness is crucial.
    Keywords: Home healthcare, peritoneal dialysis, operations research, vehicle routing problem, uncertainty, robust optimization
  • Mohammad Ali Beheshtinia *, Mehdi Ahangareian Pages 229-242
    In today's competitive market, technology transfer is an important problem for firms, organizations and governments. Therefore, making right decisions on selecting a suitable technology and designing an appropriate process to transfer it may have significant influence on the performance of organizations. In this paper, we present a new method to obtain a suitable technology transfer strategy for roller concrete road pavement using Modified Digital Logic (MDL) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Concrete pavements have been used extensively for paving highways and airports as well as business and residential streets. First, we determine the criteria and alternatives which affect technology transfer using Delphi method. Then, the attribute relative importance is calculated by MDL. Eventually, the priority of all alternatives are achieved using TOPSIS. As the result, 8 criteria (transfer cost, transfer time, technology absorbency, accessibility to market, being up-to-date along with other technologies, human resource capability, ability of providing required equipment and special political and legal conditions) and 10 available alternatives (purchasing its technical knowledge, joint venture, importing capital goods, buy back contracts, licensing, turnkey project respectively, reverse engineering, recruiting scientific and technical personnel, technical and engineering aids contracts and foreign direct investment) were identified for roller concrete road pavement technology transfer.
    Results show that human resource capability, being up-to-date along with other technologies, and the ability to provide required equipment have the greatest weight, respectively. Moreover, purchasing its technical knowledge, Joint venture and importing capital goods are the best approach for roller concrete road pavement technology transfer, respectively.
    Keywords: Transportation, concrete road pavement, technology transfer, Multi-Criteria Decision Making, TOPSIS
  • Mohammad Reza Arvin*, Mehdi Tamiz Pages 243-260
    In this paper, three-dimensional elasto-plastic finite element analysis was performed on flexible pavements under vertical repeated traffic loads to evaluate their shakedown behavior. Six different pavements with different structural number (SN) were modeled and subjected to a wide range of cyclic vehicle loads. Shakedown limits were obtained considering both failure and serviceability restraints. Results indicate that shakedown coefficient and shakedown bearing capacity increase with a rise in SN for all load types. Lower limit of shakedown bearing capacity versus SN can be regarded as a criterion for pavement design. Besides, shakedown failure-displacement factor (SFDF) was introduced as an index which is able to include both failure and serviceability criteria to compare pavements in terms of their shakedown behavior. Results suggest increase in SFDF with increasing SN, particularly for light loads. Furthermore, results indicate that increase in asphalt layer thickness always improves shakedown bearing capacity, while increase in base and subbase layer thickness is not only ineffective beyond an effective thickness but may also be damaging. In addition, the results of the present study were compared to lower bound and upper bound shakedown analysis for verification and showed reasonable agreement.
    Keywords: Pavement, shakedown, Repeated load, Elasto-plastic, Finite element
  • Yasamin Ghane, Mehdi Fallah Tafti *, Ali Mostafaeipour Pages 261-273
    The solutions used to solve bi-level congestion pricing problems are usually based on heuristic network optimization methods which may not be able to find the best solution for these type of problems. The application of meta-heuristic methods can be seen as viable alternative solutions but so far, it has not received enough attention by researchers in this field. Therefore, the objective of this research was to compare the performance of two meta-heuristic algorithms namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), with each other and also with a conventional heuristic method in terms of degree of optimization, computation time and the level of imposed tolls. Hence, a bi-level congestion pricing problem formulation, for simultaneous optimization of toll locations and toll levels on a road network, using these two meta-heuristic methods, was developed. In the upper level of this bi-level problem, the objective was to maximize the variation in the Net Social Surplus (NSS) and in the lower level, the Frank-Wolfe user equilibrium method was used to assign traffic flow to the road network. PSO and GA techniques were used separately to determine the optimal toll locations and levels for a Sioux Falls network. The numerical results obtained for this network showed that GA and PSO demonstrated an almost similar performance in terms of variation in the NSS. However, the PSO technique showed 45% shorter run time and 24% lower mean toll level and consequently, a better overall performance than GA technique. Nevertheless, the number and location of toll links determined by these two methods were identical. Both algorithms also demonstrated a much better overall performance in comparison with a conventional heuristic algorithm. The results indicates the capability and superiority of these methods as viable solutions for application in congestion pricing problems.
    Keywords: Congestion Pricing, Optimal Toll Location, Optimal Toll Level, Particle Swarm Optimization, Genetic Algorithm
  • Somayyeh Danesh Asgari, Abdorrahman Haeri *, Mostafa Jafari Pages 275-299
    With the expansion of cities and ever-increasing traffic dilemma closely connected to people’s lives, public transportation has become one the essential needs of communities. Subway because of its benefits is an important part of our lives: alleviating urban transit pressure, high safety and reliability, mass transit capacity, low energy consumption, and low price. Therefore, its performance improvement led to increasing citizenry satisfaction seems essential. The most important point in evaluation and performance improvement is the proper selection of measures. The main purpose of this paper is to introduce a new approach for selection of right indicators. For this purpose, with respect to the cause and effect relationships in balanced scorecard, its measures are applied as input and output variables of three-stage data envelopment analysis model. At first, some indicators are supposed for each BSC’s aspects and the efficiency of all stages in this basic model is computed. Then, individual inputs are considered in each stage and the efficiency of that stage is computed again in order to compare with the efficiency score of the same stage in the basic model. With interpreting of efficiency variations in each stage, appropriate measures are determined. An experimental example which contains 10 stations of Tehran subway is provided to illustrate the implementation of this model. The results indicate that efficiency of train, concurrent consideration of average density per each passenger and waiting at the station, and simultaneous consideration of average density per each passenger and the delay per trip are appropriate measures. The proposed approach in this study helps to managers and decision makers in transportation industry to recognize right indices for performance improvement.
    Keywords: Urban Railway, Appropriate Measures, Balanced Scorecard (BSC), Three- Stage Data Envelopment Analysis (DEA), Transportation
  • Babak Mirbaha, Ghodrat Eftekhari, Sajjad Hasanpour Pages 301-318
    This paper aims to evaluate and compare the effects of different methods of ramp metering on the operational conditions of traffic flow at three levels: the network level (including the freeway and its connected ramps), the entrance ramp, and the upstream segment of the entrance. To achieve this aim, one of the most important urban freeways in the metropolis of Isfahan was selected. The traffic volume passing through this freeway and its connected ramps were determined during peak hours (7 to 9 am), and the south band flows were simulated using microscopic analysis in AIMSUN software. After calibration and validation of the model, a specific on-ramp (the entrance ramp of Samadiyeh) was reviewed as the selected ramp, by using the fixed-time plan and ALINEA algorithm at demand levels of 100%, 110% and 80%. The results indicate that for normal demand level (100% demand), ramp metering does not have a significant effect on traffic flow. Further, ramp metering significantly improved upstream traffic flow in the freeway at high demand levels (110% demand), indicating its usefulness at high demand levels. At this demand level, ramp metering leads to traffic flow deviation. At low demand (80% demand), ramp metering increased the delay time of both the freeway and the ramp, indicating the ineffectiveness of ramp metering at low demands.
    Keywords: Ramp metering, ALINEA algorithm, fixed-time plan