In operations research, the transportation problem (TP) is among the earliest and most effective applications of the linear programming problem. Unbalanced transportation problems reflect the reality of supply chain a...In operations research, the transportation problem (TP) is among the earliest and most effective applications of the linear programming problem. Unbalanced transportation problems reflect the reality of supply chain and logistics situations where the available supply of goods may not precisely match the demand at different locations. To deal with an unbalanced transportation problem (UTP), it is essential first to convert it into a balanced transportation problem (BTP) to find an initial basic feasible solution (IBFS) and hence the optimal solution. The present paper is concerned with introducing a new approach to convert an unbalanced transportation problem into a balanced one and as a consequence to obtain optimum total transportation cost. Numerical examples are provided to demonstrate the suggested method.展开更多
A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transpo...A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transportation networks with demand uncertainty. In the model, drivers are divided into two classes. The first class is not equipped with ATIS, while the second class is equipped with ATIS. Different risk-taking path choice behaviours of the two classes are studied, respectively. A corresponding mixed equilibrium traffic assignment model is formulated as a variational inequality problem in terms of path flows, which is solved by a heuristic solution algorithm. Numerical results indicate that the ATIS can influence the drivers' risk-taking path choice behaviours and the total system travel time in transportation networks with demand uncertainty. It is also found that under higher demand levels, the benefits of ATIS for network performance enhancement may be more obvious.展开更多
This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport...This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport system. For this purpose, a mathematical equation was elaborated to simulate the real system based on the school transport conditions and on the estimated results of STSDR from 15 zones of Cuenca city in Ecuador. The data used in our model was collected from several diverse sources (i.e. administrative data and survey data). The estimated results have shown that our equation has described efficiently the school transport system by reaching an accuracy of 96%. Therefore, our model is suitable for statistical estimation given adequate data and will be useful in school transport planning policy. Given that, it is a support model for making decisions which seek efficiency in supply and demand balance.展开更多
The high peak hour demand in Urban Rail Transport (URT) is usually met by supply side measures such as pushing more number of trains/cars in peak hour by the operator. This additional capacity generates more demand du...The high peak hour demand in Urban Rail Transport (URT) is usually met by supply side measures such as pushing more number of trains/cars in peak hour by the operator. This additional capacity generates more demand due to a positive elasticity of demand with respect to services. Delhi Metro Rail Corporation (DMRC), India has converted its fleet from 4 cars per train to 6 cars per train and finally to 8 cars per train on its Broad Gauge section. The ridership of the system has also witnessed double digit growth during this conversion period. The demand elasticity w.r.t services for the passengers of DMRC has been estimated as 0.512 on the basis of growth of demand and increase in capacity after adjusting for natural growth. So a 10% increase in supply results into 5% increase in capacity. A simple service elasticity model has been developed to estimate demand with increase in supply. The model has been applied to Line 2 (yellow line), the busiest line of DMRC, to estimate the demand for different level of services (trains/hour). The efficacy of supply side measures is limited by the design capacity of the system beyond which any increase in supply would require disproportionate investment. An optimum combination of supply and demand side measures would perhaps be the best way to address peak hour congestion in Urban Rail Transport.展开更多
文摘In operations research, the transportation problem (TP) is among the earliest and most effective applications of the linear programming problem. Unbalanced transportation problems reflect the reality of supply chain and logistics situations where the available supply of goods may not precisely match the demand at different locations. To deal with an unbalanced transportation problem (UTP), it is essential first to convert it into a balanced transportation problem (BTP) to find an initial basic feasible solution (IBFS) and hence the optimal solution. The present paper is concerned with introducing a new approach to convert an unbalanced transportation problem into a balanced one and as a consequence to obtain optimum total transportation cost. Numerical examples are provided to demonstrate the suggested method.
基金The National High Technology Research and Development Program of China (863 Program) (No.2006AA11Z209)Youth Science and Technology Foundation of China University of Mining and Technology (No.2007A028)Natural Science Foundation of Beijing (No.9073018)
文摘A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transportation networks with demand uncertainty. In the model, drivers are divided into two classes. The first class is not equipped with ATIS, while the second class is equipped with ATIS. Different risk-taking path choice behaviours of the two classes are studied, respectively. A corresponding mixed equilibrium traffic assignment model is formulated as a variational inequality problem in terms of path flows, which is solved by a heuristic solution algorithm. Numerical results indicate that the ATIS can influence the drivers' risk-taking path choice behaviours and the total system travel time in transportation networks with demand uncertainty. It is also found that under higher demand levels, the benefits of ATIS for network performance enhancement may be more obvious.
文摘This paper presents a new conception model of school transportation supply-demand ratio (STSDR) in order to define the number of school buses needed in a limited area and to describe the conditions of school transport system. For this purpose, a mathematical equation was elaborated to simulate the real system based on the school transport conditions and on the estimated results of STSDR from 15 zones of Cuenca city in Ecuador. The data used in our model was collected from several diverse sources (i.e. administrative data and survey data). The estimated results have shown that our equation has described efficiently the school transport system by reaching an accuracy of 96%. Therefore, our model is suitable for statistical estimation given adequate data and will be useful in school transport planning policy. Given that, it is a support model for making decisions which seek efficiency in supply and demand balance.
文摘The high peak hour demand in Urban Rail Transport (URT) is usually met by supply side measures such as pushing more number of trains/cars in peak hour by the operator. This additional capacity generates more demand due to a positive elasticity of demand with respect to services. Delhi Metro Rail Corporation (DMRC), India has converted its fleet from 4 cars per train to 6 cars per train and finally to 8 cars per train on its Broad Gauge section. The ridership of the system has also witnessed double digit growth during this conversion period. The demand elasticity w.r.t services for the passengers of DMRC has been estimated as 0.512 on the basis of growth of demand and increase in capacity after adjusting for natural growth. So a 10% increase in supply results into 5% increase in capacity. A simple service elasticity model has been developed to estimate demand with increase in supply. The model has been applied to Line 2 (yellow line), the busiest line of DMRC, to estimate the demand for different level of services (trains/hour). The efficacy of supply side measures is limited by the design capacity of the system beyond which any increase in supply would require disproportionate investment. An optimum combination of supply and demand side measures would perhaps be the best way to address peak hour congestion in Urban Rail Transport.
