Sensitivity analysis of the variable demand probit stochastic user equilibrium with multiple user classes

This paper presents a formulation of the multiple user class, variable demand, probit stochastic user equilibrium model. Sufficient conditions are stated for differentiability of the equilibrium flows of this model. This justifies the derivation of sensitivity expressions for the equilibrium flows, which are presented in a format that can be implemented in commercially available software. A numerical example verifies the sensitivity expressions, and that this formulation is applicable to large networks

Second best toll and capacity optimisation in network: solution algorithm and policy implications

This paper looks at the first and second-best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second-best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second-best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network

Chinese herbal recipe versus diclofenac in symptomatic treatment of osteoarthritis of the knee: a randomized controlled trial [ISRCTN70292892]

BACKGROUND: Duhuo Jisheng Wan (DJW) is perhaps the best known and most widely used Chinese herbal recipe for arthralgia, but the clinical study to verify its efficacy is lacking. The purpose of this study was to compare the efficacy of DJW versus diclofenac in symptomatic treatment of osteoarthritis (OA) of the knee. METHODS: This study was a randomized, double-blind, double-dummy, controlled trial. The 200 patients suffering from OA of the knee, were randomized into the DJW and diclofenac group. The patients were evaluated after a run-in period of one week (week 0) and then weekly during 4 weeks of treatment. The clinical assessments included visual analog scale (VAS) score that assessed pain and stiffness, Lequesne's functional index, time for climbing up 10 steps, as well as physician's and patients' overall opinions on improvement. RESULTS: Ninety four patients in each group completed the study. In the first few weeks of treatment, the mean changes in some variables (VAS, which assessed walking pain, standing pain and stiffness, as well as Lequesne's functional index) of the DJW group were significantly lower than those of the diclofenac group. Afterwards, these mean changes became no different throughout the study. Most of the physician's and patients' overall opinions on improvement at each time point did not significantly differ between the two groups. Approximately 30% of patients in both groups experienced mild adverse events. CONCLUSION: DJW demonstrates clinically comparable efficacy to diclofenac after 4 weeks of treatment. However, the slow onset of action as well as approximately equal rate of adverse events to diclofenac might limit its alternative role in treatment of OA of the knee

A Genetically Hard-Wired Metabolic Transcriptome in Plasmodium falciparum Fails to Mount Protective Responses to Lethal Antifolates

Genome sequences of Plasmodium falciparum allow for global analysis of drug responses to antimalarial agents. It was of interest to learn how DNA microarrays may be used to study drug action in malaria parasites. In one large, tightly controlled study involving 123 microarray hybridizations between cDNA from isogenic drug-sensitive and drug-resistant parasites, a lethal antifolate (WR99210) failed to over-produce RNA for the genetically proven principal target, dihydrofolate reductase-thymidylate synthase (DHFR-TS). This transcriptional rigidity carried over to metabolically related RNA encoding folate and pyrimidine biosynthesis, as well as to the rest of the parasite genome. No genes were reproducibly up-regulated by more than 2-fold until 24 h after initial drug exposure, even though clonal viability decreased by 50% within 6 h. We predicted and showed that while the parasites do not mount protective transcriptional responses to antifolates in real time, P. falciparum cells transfected with human DHFR gene, and adapted to long-term WR99210 exposure, adjusted the hard-wired transcriptome itself to thrive in the presence of the drug. A system-wide incapacity for changing RNA levels in response to specific metabolic perturbations may contribute to selective vulnerabilities of Plasmodium falciparum to lethal antimetabolites. In addition, such regulation affects how DNA microarrays are used to understand the mode of action of antimetabolites

A Metaheuristic Framework for Bi-level Programming Problems with Multi-disciplinary Applications

Bi-level programming problems arise in situations when the decision maker has to take into account the responses of the users to his decisions. Several problems arising in engineering and economics can be cast within the bi-level programming framework. The bi-level programming model is also known as a Stackleberg or leader-follower game in which the leader chooses his variables so as to optimise his objective function, taking into account the response of the follower(s) who separately optimise their own objectives, treating the leader’s decisions as exogenous. In this chapter, we present a unified framework fully consistent with the Stackleberg paradigm of bi-level programming that allows for the integration of meta-heuristic algorithms with traditional gradient based optimisation algorithms for the solution of bi-level programming problems. In particular we employ Differential Evolution as the main meta-heuristic in our proposal.We subsequently apply the proposed method (DEBLP) to a range of problems from many fields such as transportation systems management, parameter estimation and game theory. It is demonstrated that DEBLP is a robust and powerful search heuristic for this class of problems characterised by non smoothness and non convexity

Evaluation and Design of Transport Network Capacity Under Demand Uncertainty

A flexible evaluation and design model for transport network capacity under demand variability is proposed. The future stochastic demand is assumed to follow a normal distribution. Traveler path choice behavior is assumed to follow the probit stochastic user equilibrium. The network reserve capacity is used to evaluate the performance of the network. Since the future demand is stochastic, the reserve capacity is measured by possible increases in both mean and standard deviation (SD) of the base demand distribution. The proposed model therefore represents the flexibility of the network in its robustness to origin-destination demand variation (i.e., high SD). The proposed model can also determine an optimal network design to maximize the reserve capacity of the network for both the mean and the SD of the increased demand distribution. The implicit programming approach is applied to solve the optimization problem. Sensitivity analysis is adopted to provide all necessary derivatives. The model and algorithm are tested with a hypothetical network to illustrate the merits of the proposed model

On the existence and uniqueness of first best tolls in networks with multiple user classes and elastic demand

System optimal (SO) or first best pricing is examined in networks with multiple user classes and elastic demand, where different user classes have a different average value of value of time (VOT). Different flows (and first best tolls) are obtained depending on whether the SO characterisation is in units of generalised time or money. The standard first best tolls for time unit system optimum are unsatisfactory, due to the fact that link tolls are differentiated across users. The standard first best tolls for the money unit system optimum may seem to be practicable, but the objective function of the money unit system optimum is nonconvex, leading to possible multiple optima (and non-unique first best tolls). Since these standard first best tolls are unsatisfactory, we look to finding common money tolls which drive user equilibrium flows to time unit SO flows. Such tolls are known to exist in the fixed demand case, but we prove that such tolls do not exist in the elastic demand case. Although common money tolls do not exist which drive the solution to the exact time system optimal flows, tolls do exist which can push the system close to time system optimum (TSO) flows

A real-time bus arrival time information system using crowdsourced smartphone data : a novel framework and simulation experiments

2017-2018 > Academic research: refereed > Publication in refereed journal201802 bcrcAccepted ManuscriptRGCPublishe