Capacity Restraint Research Articles

Early Childhood Education Degree programme for Non-State Higher Education Institutes in Sri Lanka – Need Survey

Early Childhood Education (ECE) is the foundation of education which helps to develop the child’s cognitive, emotional, and physical aspects. Unquestionably ECE educators play a vital role. Hence, teacher education in early childhood context is very important. However currently in Sri Lanka only very few state universities conduct Bachelor of Education in ECE and Primary Education and while other Non-State Higher Education institutes (NSHEIs) offer Early Childhood Education degrees affiliated to foreign universities. Further, presently no NSHEI offer the Ministry of Education or University Grants Commission approved degree in Early Childhood Education. Hence in this context objective of the study is to investigate the need for the Bachelor of Education ECE Degree programme at NSHEI in Sri Lanka. Study conducted in one of the prominent NSHEIs (ABC institute) in Sri Lanka. Therefore, Case study method adopted, and quantitative measures have been complemented with the qualitative measures. Sample size is seventy-five student teachers at ABC institute. This is a survey research and data collection methods are questionnaire for student teachers and key informant interviews conducted with some key stakeholders in the state universities and three preschool owners in Colombo district. Results of the study revealed that benefits of the ECE Degree to students and for the country and emphasized it is very crucial to commence the ECE programme as it provides more opportunities to students since few opportunities and capacity restraint in state universities. Furthermore, study highlighted that ninety six percent student like to start ECE Degree and if the institute commence the programme ninety percent student would like to join the programme. Therefore, study can be concludedthat ABC as a NSHEI there is a good potential and opportunity to proceed with the ECE Degree and contribute to the foundation of the education in the country which add value to the system.

Multi-depot vehicle scheduling with multiple vehicle types on overlapped bus routes

In China, overlapped routes from multiple bus lines are widespread. Some buses are overcrowded while others have few passengers. The goal of this study is to reduce onboard passenger crowding without wasting bus capacity. This paper examines an extended multiple-depot vehicle scheduling problem (VSP) with multiple vehicle types. First, a bi-objective integer programming model was created. The trade-off between operating cost and passenger travel cost was established and the crowding cost due to different vehicle sizes was especially considered. Then, the capacity restraint incremental assignment algorithm and a vehicle scheduling method with multiple vehicle types were developed to find Pareto-optimal solutions that considered vehicle capacity constraints. Finally, the proposed methodology was validated using a real-world transit network in Beijing, China. The optimization results from about 1.18 million bus card swiping records show that our model and solution algorithm can effectively reduce the passenger crowding cost and avoid the waste of transport capacity.

Study of bond-slip performance and ultimate bearing capacity calculation under static and reciprocating action of folded perfobond shear keys

The PBL (Perfobond Leiste) shear key has advantages such as high load capacity and high restraint capacity. However, at the same time, there are also problems such as insufficient deformation capacity and low stiffness along the weak axis direction. In addition, shear key performance degradation, ductility, and other problems are not yet clear under the reciprocal seismic action. To this end, a folded perfobond shear key is proposed in this paper to solve the problems of insufficient deformation capacity and uneven stiffness distribution of the traditional PBL shear key. At the same time, numerical analysis is carried out to investigate the seismic performance of the shear key under earthquakes, such as stiffness degradation, ductility, and energy dissipation. Through the push-out test, it is found that the steel plate outside the shear key deforms, showing a certain semi-rigid characteristic; concrete forms a trapezoidal constraint area centered on shear keys, and the constraint effect is significantly improved compared with the point constraint of studs. On the whole, under the condition of a similar shear section, the bearing capacity of the shear key is 1.5 times that of the stud. The ductility coefficient is above 3.0, showing good deformation ability. Through parameter analysis, it is found that the bearing capacity of shear keys increases with the increase of web width-thickness ratio, but the deformation capacity degenerates. The opening rate mainly affects the embedded effect of shear keys and concrete. Based on the fitting analysis, the variation laws of web width influence coefficient γB, web height influence coefficient γH, and embedded effect influence coefficient γD are obtained, and the calculation formula of shear key bearing capacity is proposed. Finally, based on the push-out test, the hysteretic behavior of the shear key is studied. It is found that the load-displacement hysteretic curve of the shear key is full, the ductility coefficient is 4.2, and the equivalent viscous damping coefficient is 0.27, which shows good seismic capacity. In summary, the new shear key realizes the good unity of bearing capacity and deformation and has high engineering application value.

Evaluating Road Networks Performance: Capacity Restraint Method

Traffic condition in Yogyakarta City faces growing volume each year. Meanwhile, the development of road is increasingly harder to expand due to limited availability of lands and funds. Therefore, evaluation of road networks is needed to avoid, reduce and eliminate traffic congestion in Yogyakarta. In this study, the authors aim to build road network model representing traffic condition in Yogykarta. Capacity restraint method is used for traffic assignment with the assistance of ZIN software. ZIN capability to model complex road networks is also assessed.

Towards an Optimal IPO Mechanism

Concerns about the negative consequences of the excessive underpricing of the current arrangement in the initial public offering (IPO) market for the provision of entrepreneurial finance—book building—have led to research into the viability of auctions for IPO pricing and allocation. IPO firms face a trade-off between the benefit of accurate and reliable IPO price discovery and the cost of underpricing. The main aim of this paper was to gain new scientific knowledge about this trade-off by measuring the impact of two key variables on this trade-off: capacity restraint and discount on the auction clearing price. Using controlled experiment methodology in multi-unit uniform price auctions we found that the most capacity-restricted auctions that also offer investors a discount are likely to produce the most accurate and reliable price discovery and consequently, the most predictable auction outcome. There are indications that a discount of 8% may suffice to incentivize investors to reliably contribute to price discovery. The resulting underpricing (and its variability) of these auctions is likely to be significantly lower than if book building would be used to price and allocate IPOs. Technological innovation in the IPO market through the application of recent advances in data science, experimental economics and artificial intelligence allows for the optimization of IPO mechanisms and crowdfunding platforms which in turn improves the access to equity required for entrepreneurial finance.

Optimal Location of Fast Charging Stations for Mixed Traffic of Electric Vehicles and Gasoline Vehicles Subject to Elastic Demands

With the rapid development of electric vehicles (EVs), one of the urgent issues is how to deploy limited charging facilities to provide services for as many EVs as possible. This paper proposes a bilevel model to depict the interaction between traffic flow distribution and the location of charging stations (CSs) in the EVs and gasoline vehicles (GVs) hybrid network. The upper level model is a maximum flow-covering model where the CSs are deployed on links with higher demands. The lower level model is a stochastic user equilibrium model under elastic demands (SUE-ED) that considers both demands uncertainty and perceived path constraints, which have a significant influence on the distribution of link flow. Besides the path travel cost, the utility of charging facilities, charging speed, and waiting time at CSs due to space capacity restraint are also considered for the EVs when making a path assignment in the lower level model. A mixed-integer nonlinear program is constructed, and the equivalence of SUE-ED is proven, where a heuristic algorithm is used to solve the model. Finally, the network trial and sensitivity analysis are carried out to illustrate the feasibility and effectiveness of the proposed model.

Research on resource service matching in cloud manufacturing

Resource Service Matching is one of the key issues in Cloud Manufacturing, which is the latest mode of network manufacturing. In this paper, Resource Service Matching for aggregated resources with capacity restraint is discussed. Genetic Algorithms is proposed to search the best matching result for the request of customers, which assure the total cost and time of all the tasks is the lowest. In order to avoid premature evolution of populations, a novel approach of Genetic Algorithm is proposed in this paper. It is indicated by the results of simulation that the improved algorithm worked efficiently in Resource Service Matching.

The research on under water resources supporting capacity restraint in Xi’an city of the water sports

The research on under water resources supporting capacity restraint in Xi’an city of the water sports

Effects of rotational capacity and horizontal restraint on development of catenary action in 2-D RC frames

Research studies on 2-D reinforced concrete (RC) beams under middle column removal scenarios have found that catenary action (CA) can significantly increase structural resistance and deflection beyond flexural capacity. However, development of CA is highly dependent on the rotational capacity of RC beams and the degree of horizontal restraints from adjacent structures. Previous studies have identified the effect of varying beam details, (such as geometry and reinforcement ratio) on CA, but very few publications focused on the beneficial effect of rotational capacity on CA. To the authors’ best knowledge, there has not been any publication on quantifying the effect of rotational capacity on CA. Moreover, experimental studies of CA have so far been conducted on RC beams with full restraints at the two supporting ends. Hence, in this study, five RC frame specimens were tested to study the effects of rotational capacity and degree of horizontal restraint on CA. One frame served as a control specimen, two specimens for improvement in rotational capacity, and another two with inadequate horizontal restraint. Improvement in rotational capacity was engineered in one frame through provision of closer-spaced stirrups near to the joints and another frame through substitution of deformed bars with smooth round bars. Adverse effect of inadequate horizontal restraint was investigated under penultimate column removal scenarios. Through the testing and analysis of the five frames, the effects of improvement in rotational capacity and inadequate horizontal restraint on CA could be quantified and discussed. Finally, practical suggestions on enhancing CA through detailing were provided.

Comparison of Different Mode Choice Models for Work Trips using Data Mining Process

Objectives: An attempt made in this paper to compare the prediction ability of different mode choice behaviour models of commuters' work trip. Methods/Statistical Analysis: The personal characteristics like age, income, family size, occupation of commuters and the trip characteristics such as trip time and trip cost were selected as independent variables. Four types of alternative modes were considered for developing the models such as private car, two wheelers, Shared Auto and bus. The behaviour predicting ability of three different models namely boost tree, MNL and SVM model compared using data mining process in Statistica software. Findings: We found that the boost tree model is superior among all. Applications/Improvements: Next step would be to find and to put the probabilities of each mode for each zone. Further to assign the route using all or nothing assignment method or capacity restraint assignment method.

The Freight Train Routing Problem for Congested Railway Networks with Mixed Traffic

We consider the following freight train routing problem (FTRP). Given is a transportation network with fixed routes for passenger trains and a set of freight trains (requests), each defined by an origin and destination station pair. The objective is to calculate a feasible route for each freight train such that the sum of all expected delays and all running times is minimal. Previous research concentrated on microscopic train routings for junctions or inside major stations. Only recently approaches were developed to tackle larger corridors or even networks. We investigate the routing problem from a strategic perspective, calculating the routes in a macroscopic transportation network of Deutsche Bahn AG. In this context, macroscopic refers to an aggregation of complex and large real-world structures into fewer network elements. Moreover, the departure and arrival times of freight trains are approximated. The problem has a strategic character since it asks only for a coarse routing through the network without the precise timings. We provide a mixed-integer nonlinear programming (MINLP) formulation for the FTRP, which is a multicommodity flow model on a time-expanded graph with additional routing constraints. The model’s nonlinearities originate from an algebraic approximation of the delays of the trains on the arcs of the network by capacity restraint functions. The MINLP is reduced to a mixed-integer linear model (MILP) by piecewise linear approximation. The latter is solved by a state-of-the art MILP solver for various real-world test instances.

AN ASSESSMENT OF DISINCENTIVE POLICY ON SLOT ALLOCATION SYSTEM IN INDONESIAN AIRPORTS

Indonesian airports have been experiencing significant air traffic growth and are unable to cope with the increasing air passenger demand. There is an urgent need for an effective slot allocation strategy to manage the demand for airport capacity. This paper conducts a case study to examine the possibility of managing slot time allocation to maximize runways capacity by analyzing disincentive strategy in balancing the usage of runways with Capacity Restraint and Demand Balanced approach. The research found that airlines willing to use slot time at the most demanded time interval should pay an additional 6.57% (CR approach) from total revenue gained by the government from slot sector and 6.55% (DB approach). The additional cost for less demanded slot time interval is only 0.09% (in both CR and DB approaches). Findings from this study should be considered as an initial step toward educating policy makers and airport authorities with the aims to creating better mechanism in Indonesia’s airspace market.

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Influence of Capacity Restraint Functions on Traffic Distribution and Their Practical Use in the Traffic Modelling

The article deals with the issue of capacity restraint functions (curves) determining for roads and their use in the transport model. It describes the procedure for obtaining traffic flow characteristics and the derivation of the parameters needed to create basic restraint BPR function (Bureau of Public Roads). New parameters were then used in traffic assignment process. The impact of parameter changes for routes redistribution on traffic network was evaluated in detail.The practical use of BPR function in the real traffic model is described in the second part. The article presents the method of volume-delay function definition for different model links types.

Is trust a driver for territorially embedded industrial systems? a case study of the home‐building industry in norway

Trust is said to be necessary for creating and maintaining territorially embedded industrial systems. On the basis of data for the Norwegian home‐building sector, this article analyses trust and price competition; how trust is built and dismantled; and trust and place. The main findings are that: trust and price competition interact, but trust is more important in the design and planning phases than in the construction phase; economic factors are important for building trust, together with competence and team work; and trust is related to space, partly through places embodied in trust and partly through trust embedded in places. However, this embeddedness is not like that which has long been claimed to exist in territorially embedded industrial systems, but embeddedness where trust acts as a reinforcement, contingent upon other factors, as a capacity restraint and a socially constructed need for face‐to‐face meetings.

The Norwegian Home‐building Industry — Locally Embedded or in the Space of Flows?

AbstractDuring the last 25 years the neoliberal institutional turn and globalization have caused profound structural changes and challenged our theoretical understandings. In this article the emerging structure of the Norwegian home‐building industry is presented, with a focus on the interaction between different actors in the different stages and functions of the home‐building network. The structure of employer–contractor relations in the liberalized housing market is disclosed and used as a basis for discussing the theoretical perspectives developed by Amin and Thrift’s work on circulation and distanciation and by Castells’ work on the network enterprise and space of flows. The questions asked are whether these trends are seen in the Norwegian home‐building industry. From the analysis we learn that home‐building is considered a local business due to: a capacity restraint regarding local market knowledge; the interaction with local planning authorities; face‐to‐face meetings; and social relations. On the other hand, there are a set of factors that tell a ‘circulation’ story: an increasing number of participants, especially in design and planning; a more complex market structure; and a need for developer’s knowledge on trends in design and construction. In sum, the analysis discloses a structure of increasing circulation but without a corresponding distanciation, and from Castells’ perspective there is an emerging space of flows, but still a rather local geometry; a pattern probably prone to change in the years to come.

Validation of a schedule‐based capacity restraint transit assignment model for a large‐scale network

AbstractThis paper describes the application of a capacity restraint trip assignment algorithm to a real, large‐scale transit network and the validation of the results. Unlike the conventional frequency‐based approach, the network formulation of the proposed model is dynamic and schedule‐based. Transit vehicles are assumed to operate to a set of pre‐determined schedules. Passengers are assumed to select paths based on a generalized cost function including in‐vehicle and out‐of‐vehicle time and line change penalty. The time‐varying passenger demand is loaded onto the network by a time increment simulation method, which ensures that the capacity restraint of each vehicle during passenger boarding is strictly observed. The optimal‐path and path‐loading algorithms are applied iteratively by the method of successive averages until the network converges to the predictive dynamic user equilibrium. The Hong Kong Mass Transit Railway network is used to validate the model results. The potential applications of the model are also discussed.

Optimizing the benefits of urban road user charging

Traffic congestion is a feature of most modern cities but attempts to control it or limit its effects have met with only modest success. There is significant and continuing interest in the concept of charging city vehicle users, although apart from the use of parking charges actual operational schemes are few and far between. In this paper, we compare three alternative charging policies using a simplified model of travel demand and supply, which we combine with cost benefit techniques. The charging policies are area-based charging in which users pay to locate in or enter an area, terminal-charging based on supplementary parking fees in residential and non-residential locations and distance-based charging which is a charge related to how far users travel. The model allows for behavioural effects resulting from trip diversion and demand suppression, as well as capacity restraint (speed-flow feedback effects based on limited route capacity). In the case study, we parameterize the model using data and geographical dimensions based on London. We show that area based charging delivers the least benefits whilst a hybrid policy based on terminal and distance-based charges delivers the most. Because it is of topical interest, we compare our results and predictions with the Mayor's strategy for London, which is an area-based scheme. We conclude that the revenue generated using a hybrid policy would be as great as for an area based scheme whilst at the same time delivering substantially greater benefits to road users in terms of travel time and other savings.

A capacity restraint transit assignment with elastic line frequency

This paper proposes a new formulation for the capacity restraint transit assignment problem with elastic line frequency, in which the line frequency is related to the passenger flows on transit lines. A stochastic user equilibrium transit assignment model with congestion and elastic line frequency is proposed and the equivalent mathematical programming problem is also formulated. Since the passenger waiting time and the line capacity are dependent on the line frequency, a fixed point problem with respect to the line frequency is devised accordingly. The existence of the fixed point problem has been proved. A solution algorithm for the proposed model is presented. Finally, a numerical example is used to illustrate the application of the proposed model and solution algorithm.

A probit-based stochastic user equilibrium assignment model

Stochastic methods of traffic assignment have received much less attention in the literature than those based on deterministic user equilibrium (UE). The two best known methods for stochastic assignment are those of Burrell and Dial, both of which have certain weaknesses which have limited their usefulness. Burrell's is a Monte Carlo method, whilst Dial's logit method takes no account of the correlation, or overlap,between alternative routes. This paper describes, firstly, a probit stochastic method (SAM) which does not suffer from these weaknesses and which does not require path enumeration. While SAM has a different route-finding methodology to Burrell, it is shown that assigned flows are similar. The paper then goes on to show how, by incorporating capacity restraint (in the form of link-based cost-flow functions) into this stochastic loading method, a new stochastic user equilibrium (SUE) model can be developed. The SUE problem can be expressed as a mathematical programming problem, and its solution found by an iterative search procedure similar to that of the Frank-Wolfe algorithm commonly used to solve the UE problem. The method is made practicable because quantities calculated during the stochastic loading process make the SUE objective function easy to compute. As a consequence, at each iteration, the optimal step length along the search direction can be estimated using a simple interpolation method. The algorithm is demonstrated by applying it successfully to a number of test problems, in which the algorithm shows good behaviour. It is shown that, as the values of parameters describing the variability and degree of capacity restraint are varied, the SUE solution moves smoothly between the UE and pure stochastic solutions.