Clustering intelligent transportation sensors using public transportation

Advanced transportation sensors use a wireless medium to communicate and use data fusion techniques to provide complete information. Large-scale use of intelligent transportation sensors can lead to data bottlenecks in an ad-hoc wireless sensor network, which needs to be reliable and should provide a framework to sensors that constantly join and leave the network. A possible solution is to use public transportation vehicles as data fusion nodes or cluster heads. This paper presents a mathematical programming approach to use public transportation vehicles as cluster heads. The mathematical programming solution seeks to maximize benefit achieved by covering both mobile and stationary sensors, while considering cost/penalty associated with changing cluster head locations. A simulation is developed to capture realistic considerations of a transportation network. This simulation is used to validate the solution provided by the mathematical model.     

需求区间型运输问题的求解算法

为了便于建立与需求区间型运输问题有关的决策支持系统，本给出了一个求解需求区间型运输问题的数值算法，证明了算法的理论依据，并举例说明算法的应用，该算法能求得问题的最优解，并具有易于编程实现、收敛性好等优点，大量数值实验表明该算法有较高的计算效率。     

Weber problems with alternative transportation systems

In this paper we address a planar p-facility location problem where, together with a metric induced by a gauge, there exists a series of rapid transit lines, which can be used as alternative transportation system to reduce the total transportation cost. The location problem is reduced to solving a finite number of (multi)-Weber problems, from which localization results are obtained. In particular, it is shown that, if the gauge in use is polyhedral, then the problem is reduced to finding a p-median.     

求解网络最大流问题的一个算法

为了便于建立与网络最大流问题有关的决策支持系统，本给出一个求解网络最大流问题的数值算法。证明了算法的理论依据，并举例说明了算法的应用。该算法能求出网络最大流和最小截，并具有易于编程实现、收敛性好等优点，大量数值实验表明该算法非常实用有效。     

Strategic route extension in transit networks

This study proposes a methodology through which transportation analysts and policy makers can use spatial optimization to support strategic planning, with the goal of extending existing service networks. Based on modeling objectives common to many service industries, an approach is developed for integrating geographic information systems (GIS) and spatial optimization modeling in order to extend an existing transit system through prioritizing route and stop additions. Development of a strategic methodology such as this is vital for agencies interested in extending transit networks to accommodate urban growth and development. This is especially true in public transit applications, such as bus route planning, as the future of bus-based public transportation depends on the success of route expansion and modification. The developed approach is applied to the transit system in Columbus, Ohio.     

Synchronized production–distribution planning in a single-plant multi-destination network

This paper examines the flow synchronization problem between a manufacturing location and multiple destinations. Multiple products can be shipped from the manufacturing location to different locations via multiple transportation modes. These transportation modes may have different transportation lead times. The transportation costs structure of the different transportation modes offer economies of scale and can be represented by general piecewise linear functions. The production system at the manufacturing location is a serial process with a bottleneck stage. At the bottleneck stage, a predetermined production sequence must be maintained as is the case in some process-based industries. We propose a tight mixed integer programming model for integrated planning of production and distribution in the network. We show that by adding simple valid inequalities and special 0-1 variables, major computational improvements can be achieved when solving this problem with commercial solvers such as Cplex. We also propose a sequential solution approach, based on the independent, but synchronized, solutions of the production and distribution sub-problems. Finally, the solution methods proposed are tested experimentally for realistic problems and the advantage of integrated planning over independent but synchronized planning is assessed.     

Combined Sea and Land Transportation

An important problem today in the field of transportation is the standardization of the cargo, e.g. by using containers, and the design of the handling and transportation equipment for the specific cargo to be transported.The paper presents a method for determining the transportation system with emphasis on sea transport. Thus the cargo is to be transported by sea from the factory to customers spread over a large region, e.g. Europe. The problem is to select the ports of call, the quantities to be delivered at the ports, as well as the size and type of vessel.This problem resembles the warehouse location problem (the location of ports) but requires in addition the determination of ship size, type of ship and whether one or more ports should be called at on each journey with a single ship. A discussion is also presented as to the possibility of considering randomness in the system with respect to customer demand and weather conditions.The method used resembles that suggested by Baumol and Wolfe for the ware-house location problem. A concave function of the quantities delivered at each port is derived and this is then shown to converge to a local optimum.An example is solved to illustrate the method.     

Selection of Alternative Fuels for Sustainable Urban Transportation under Multi-criteria Intuitionistic Fuzzy Environment

The unrestrained expansion in urbanization and increasing development of new means of transports result in major urban land use and transportation system which is socially, economically and environmentally unsustainable. Hence the major challenge for the decision makers regarding the transportation policies is to choose the alternative fuel operated vehicles resulting in a sustainable transportation system. In real life situations, it is difficult to get exact data, so to express the uncertain data, intuitionistic fuzzy data has been considered. The problem is to select the best fuel technology for land transportation subject to multiple criterions resulting in a sustainable transportation system in an uncertain environment. Here, the similarity measures of Intuitionistic fuzzy sets (IFSs) are applied for developing a methodology for identifying the best option. The weights of the attributes may be known or partially known or unknown. The unknown weights are determined by normalizing the average score functions of the intuitionistic fuzzy data for the criterion. Algorithms are given for handling different situations and numerical examples illustrate the varied cases.     

Calculation of traffic flow breakdown probability to optimize link throughput

Traffic breakdown phenomenon is prevalent in empirical traffic system observations. Traffic flow breakdown is usually defined as an amount of sudden drop in traffic flow speed when traffic demand exceeds capacity. Modeling and calculating traffic flow breakdown probability remains an important issue when analyzing the stability and reliability of transportation system. The breakdown mechanism is still mysterious to practitioners and researchers in varying manner. Treating breakdown as a random event, this paper use discrete time Markov chain (DTMC) to model traffic state transition path, as a result, a transition probability matrix can be generated from empirical observations. From empirical analysis of breakdown, we found this formulation of breakdown probability follows the Zipf distribution. Therefore, a connection from traffic flow breakdown probability to how many vehicles are occupying a certain freeway segment (e.g. a link) will be established. Following from the results, a quantitative measure of breakdown probability can be obtained to optimize ramp metering rates to achieve optimum system performance measures.     

Using intelligent agents for pro-active,real-time urban intersection control

The usability and effectiveness of traffic control systems greatly depends on its ability of reacting upon traffic patterns and permutations. In this research we investigate the applicability of autonomous intelligent agents in Urban Traffic Control (UTC), and why these artificial intelligent strategies are useful in UTC. We propose a system that autonomously can adapt itself, based upon internal rules and its environment, at changing environments. Both long term changes as well as short term changes are accounted for in different manner. The UTC model is primarily based on several Intelligent Traffic Signalling Agents (ITSA) and some authority agents. This approach enables us to use a UTC system, based on agent technology, capable of responding to traffic conditions in real-time. The system can maintain its integrity and stability within the overall transportation system. Due to its pro-active behaviour we are able to make better use of the capacity of intersections.     

Performance Optimization of a Class of Discrete Event Dynamic Systems Using Calculus of Variations Techniques

We explore an approach involving the use of calculus of variations techniques for discrete event dynamic system (DEDS) performance optimization problems. The approach is motivated by the observation that such problems can be described by separable cost functions and recursive dynamics of the same form as that used to describe conventional discrete-time continuous-variable optimal control problems. Three important difficulties are that DEDS are generally stochastic, their dynamics typically involve max and min operations, which are not everywhere differentiable, and the state variables are often discrete. We demonstrate how to overcome these difficulties by applying the approach to a transportation problem, modeled as a polling system, where we are able to derive an explicit and intuitive analytic expression for an optimal control policy.     

基于货物分类配送的电动汽车路径优化与换电策略研究

电动汽车参与的物流配送服务需要统筹协调车辆路径、配送对象与换电策略。本文提出了考虑货物分类需求的电动汽车路径优化与换电策略问题,并建立了该问题的整数规划数学模型。其次,提出了基于禁忌搜索-改进节约算法的两阶段混合启发式算法MCWTS和一种四阶段启发式算法IGALNS。通过多组小规模算例验证了算法的有效性。随后,分别从运营成本、路径距离、换电策略以及混合运输线路等方面比较并分析了货物分类对运营策略的影响。实验结果表明,该模型可以在配送距离略有增加的情况下避免将不适宜混合运输的货物指派给同一车辆,达到降低货物运输损失提高顾客满意度的目的。最后,通过多组较大规模算例对两种启发式算法的有效性进行了比较。     

Fuzzy graphs modelling for HazMat telegeomonitoring

Telegeomonitoring system development combines two heterogeneous technologies: the geographical information systems technology (GIS) and telecommunications technology. In this paper, we give the system components for telegeomonitoring transportation of hazardous materials. The telegeomonitoring system uses GIS to capture civil infrastructure (urban network, land use, industries, etc.) and decision support systems technology to allow risks analysis and evaluate routing strategies that minimize transportation risk. Routing algorithms are to this effect adapted to graphs of the fuzzy risk. A new algebraic structure is proposed to solve a path-finding problem in a fuzzy graph. This algebraic structure is adapted precisely to solve the problem of the K-best fuzzy shortest paths. The approach that we proposed, consists of defining generic structures of operator’s traversal problem in fuzzy graphs. The principal contribution of our approach is to build adequate structures of path algebra to solve the problem of graph traversal in a fuzzy graph without negative circuits. Foundations of the system studied in this work will be able to be transposed to other fields of transportation.     

Improved chromosome classification using monotonic functions of mahalanobis distance and the transportation method

It is shown that the accuracy of chromosome classification constrained by class size can be improved over previously reported results by a combination of straightforward modifications to previously used methods. These are (i) the use of the logarithm of the Mahalanobis distance of an unknown chromosome's feature vector to estimated class mean vectors as the basis of the transportation method objective function, rather than the estimated likelihood; (ii) the use of all available features and full estimated covariance to compute the Mahalanobis distance, rather than a subset of features and the diagonal (variance) terms only; (iii) a modification to the way the transportation model deals with the constraint on the number of sex chromosomes in a metaphase cell; and (iv) the use of a newly discovered heuristic to weight off-diagonal elements of the covariance; this proved to be particularly valuable in cases where relatively few training examples were available to estimate covariance. The methods have been verified using 5 different sets of chromosome data.     

Capacitated location model with online demand pooling in a multi-channel supply chain

This paper presents a location model that assigns online demands to the capacitated regional warehouses currently serving in-store demands in a multi-channel supply chain. The model explicitly considers the trade-off between the risk pooling effect and the transportation cost in a two-echelon inventory/logistics system. Keeping the delivery network of the in-store demands unchanged, the model aims to minimize the transportation cost, inventory cost, and fixed handling cost in the system when assigning the online demands. We formulate the assignment problem as a non-linear integer programming model. Lagrangian relaxation based procedures are proposed to solve the model, both the general case and an important special case. Numerical experiments show the efficiency of our algorithms. Furthermore, we find that because of the pooling effect the variance of in-store demands currently served by a warehouse is an important parameter of the warehouse when it is considered as a candidate for supplying online demands. Highly uncertain in-store demands, as well as low transportation cost per unit, can make a warehouse appealing. We illustrate with numerical examples the trade-off between the pooling effect and the transportation cost in the assignment problem. We also evaluate the cost savings between the policy derived from the model, which integrates the transportation cost with the pooling effect, and the commonly used policy, which is based only on the transportation cost. Results show that the derived policy can reduce 1.5–7.5% cost in average and in many instances the percentage of cost savings is more than 10%.     

Design of an IT-driven decision support system for vehicle routing and scheduling

This paper presents the development of a decision support system used by an oil downstream company for routing and scheduling purposes. The studied problem refers to a complex delivery process of oil products from a number of distribution centers to all customers. The latest rapid advance of operations research (OR) applications, in the form of advanced planning and scheduling (APS) systems, has shown that OR algorithms can be applied in practice if (a) they are embodied in packaged information technology (IT) solutions, (b) the interface problems to mainstream ERP software applications are solved. In this study the utilisation of advanced IT systems supports effectively the planning and management of distribution operations. The combination of a supply chain management (SCM) application with a geographical information system (GIS) integrated with an enterprise resource planning (ERP) software resulted to this innovative decision support tool. The objectives of this new tool are: optimum use of the distribution network resources, transportation cost reduction and customer service improvement. The paper concludes with the benefits of the new system, emphasising at how new technologies can support transportation processes with the help of operations research algorithms embedded in software applications.     

An adaptive robust controller for time delay maglev transportation systems

For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov–Krasovskii synthesis method, therefore asymptotic stability is guaranteed.     

Solving the minimum toll revenue problem in real transportation networks

As a means to relieve traffic congestion, toll pricing has recently received significant attention by transportation planners. Inappropriate use of transportation networks is one of the major causes of network congestion. Toll pricing is a method of traffic management in which traffic flow is guided to proper time and path in order to reduce the total delay in the network. This article investigates a method for solving the minimum toll revenue problem in real and large-scale transportation networks. The objective of this problem is to find link tolls that simultaneously cause users to efficiently use the transportation network and to minimize the total toll revenues to be collected. Although this model is linear, excessive number of variables and constraints make it very difficult to solve for large-scale networks. In this paper, a path-generation algorithm is proposed for solving the model. Implementation of this algorithm for different networks indicates that this method can achieve the optimal solution after a few iterations and a proper CPU time.     

Spectral analysis for performance evaluation in a bus network

This paper deals with the performance evaluation of a public transportation system in terms of waiting times at various connection points. The behaviour of a bus network is studied in the framework of Discrete Event Systems (DES). Two possible operating modes of buses can be observed at each connection stop: periodic and non-periodic mode. Two complementary tools, Petri nets and (max, +) algebra, are used to describe the network by a non-stationary linear state model. This one can be solved after solving the structural conflicts associated to the graphical representation. From the characteristic matrix of the mathematical model, we determine eigenvalues and eigenvectors that we use to evaluate the connection times of passengers. This work is finally illustrated with a numerical example.     

Design and implementation of a decision support system for multistage investment in Chinese coal production and transportation

At present, coal production and transportation is the bottleneck in the drive to develop the Chinese economy. We formulate the multistage investment problem as a fixed charge transshipment problem with side constraints. By a special transformation, the problem can be solved via an equivalent 0–1 generalized network problem. Therefore, it can be solved quite efficiently. In implementing the 0–1 generalized network, a new heuristic method is used in selecting branch variables. The system is implemented and shown to be very efficient. The entire system is automatic and requires no manual intervention.