Linking Incidents to Customers (LINC): An Algorithm for Linking Incidents to Rail Customer Delays Inspired by Traffic Flow Theory

Rail transit agencies have greatly advanced the ability to measure delays to rail system customers and have developed key performance indicators for rail systems based on customer travel time. The ability for operators to link these customer delay metrics to root causes would provide great benefit to agencies, from incident response improvement to capital program prioritization. This paper describes a method for linking late train arrivals to both late customers and incident tickets. Inspired by traffic flow theory, the method identifies impact zones in time and space that can then be linked to a potential root cause by way of incident tickets. This algorithm is currently under development by the Washington Metropolitan Area Transit Authority’s Office of Planning, and its outputs are being integrated into a variety of operations- and capital-related business processes.

Dynamic Inventory Routing and Pricing Problem with a Mixed Fleet of Electric and Conventional Urban Freight Vehicles

Urban freight transport is essential for supporting our society regarding providing the daily needs of consumers and local businesses. In addition, it allows for the movement of goods, is distributed within urban environments, provides thousands of jobs, and supports economic growth. However, a number of issues are associated with urban freight transport, including environmental impacts, road congestion, and land use of freight facilities that conflicts with residential land use. Electric freight vehicles create zero emissions and provide a sustainable delivery system in comparison with conventional freight vehicles. In this study, a novel dynamic inventory routing and pricing problem under a mixed fleet of electric and conventional vehicles was formulated to minimize the total travel and charging costs. The proposed model is capable of deciding on replenishment times and amounts and vehicle routes. We aimed to determine the maximum social welfare (SW) capable of providing an optimal trade-off between the supplier cost and customer delay that uses a mixed fleet of vehicles. Our computational study was conducted on real data generated from a delivery dataset in Tehran. Under the proposed policy with a fleet of only electric vehicles, the SW increased by 3% while the average customer delay reduced by 15% compared with a fleet of conventional vehicles. The results show that the number of served customers and customer delay would be affected by transitioning conventional urban freight vehicles to electric vehicles. Therefore, the proposed delivery system has a significant impact on energy savings and emissions.

Labor Welfare in On-Demand Service Platforms

Problem definition: An on-demand service platform relies on independent workers (agents) who decide how much time, if any, to devote to the platform. Some labor advocates have argued that an expansion of the labor pool hurts agents—by reducing the wage and agent utilization (i.e., the fraction of time an agent is busy serving customers). Motivated by concern for agent welfare, regulators are considering measures that reduce the labor pool size or that impose a floor on the nominal wage or effective wage (i.e., the product of the nominal wage and agent utilization). Are agents indeed hurt by an expansion in the labor pool size? Which type of wage-floor regulation is preferable? Are consumers hurt by the imposition of a wage floor? Academic/practical relevance: Because independent agents work without the traditional protections intended to ensure the welfare of employees, the welfare of those agents is an important concern. Methodology: We employ an equilibrium model that accounts for the interaction among price, wage, labor supply, customer delay, and demand. Results: Average labor welfare increases and then decreases in the labor pool size; that is, agents are harmed by an expansion in the labor pool size if and only if the labor pool size is sufficiently large. The effective wage floor is superior to the nominal wage floor in terms of labor welfare maximization. More generally, the two types of wage floors have structurally different effects on labor welfare, with a floor on the nominal wage only beneficial to agents if it is sufficiently small. Contrary to the conventional view that consumers are hurt by an effective wage floor (because they face a higher price, due to upward pressure on the wage, and longer delay, due to upward pressure on agent utilization), consumers actually benefit. Managerial implications: Regulators, labor advocates, platform managers, and agents benefit from understanding the forces that create and destroy labor welfare.

A Virtualized Target Queuing Balanced Model Using Vmax/M/G-Load(Min)/Cache-P2λM for Reducing Queuing Time Expectation of Customer Delay Tolerance

Queuing theory is a formal mathematical model of late response arrival of customer waiting in various access services, accepting processes management as a whole field. Often multiple server sorting can be used to estimate the number of servers and service rates be high due too lacking of time, with an average delay sequence in the analysis. Using these sequence models to read more than one sequence during execution approximates system sorting performance. To resolve this problem we modulated the distributed process into Virtualized Target Queuing Balanced Model (VTQBM) using Vmax/M/G-Load (Min)/Cache-P2λM for reducing queuing time expectation of customer delay tolerance. The Virtual Resource queuing System is optimized with fork-join queue by creating single to multimodal service performance using target request load balancer in a shared distribution mode. Sorting the request buffer cache is created based on Customer Request Arrival Rate (CRAR) and resource output preferred to check with target rule waiting in the Load balancer. To improve the use of model complex virtual resource sharing shared with customer arrival to Cache Target Load Allocator (CTLA) on queuing distributed resources, This fork joiner target the service performance to reduce the customer waiting time in queuing and produce outputs can achieve a different parameter input transformation on queuing theory.

Exact simulation of the stationary distribution of the FIFO M/G/c queue

We present an exact simulation algorithm for the stationary distribution of the customer delayDfor first-in–first-out (FIFO) M/G/cqueues in which ρ=λ/μ<1. We assume that the service time distributionG(x)=P(S≤x),x≥0 (with mean 0<E(S)=1/μ<∞), and its corresponding equilibrium distributionGe(x)=μ∫0xP(S>y)dyare such that samples of them can be simulated. We further assume thatGhas a finite second moment. Our method involves the general method of dominated coupling from the past (DCFTP) and we use the single-server M/G/1 queue operating under the processor sharing discipline as an upper bound. Our algorithm yields the stationary distribution of the entire Kiefer–Wolfowitz workload process, the first coordinate of which isD. Extensions of the method to handle simulating generalized Jackson networks in stationarity are also remarked upon.

Exact simulation of the stationary distribution of the FIFO M/G/c queue

We present an exact simulation algorithm for the stationary distribution of the customer delay D for first-in–first-out (FIFO) M/G/c queues in which ρ=λ/μ<1. We assume that the service time distribution G(x)=P(S≤x),x≥0 (with mean 0<E(S)=1/μ<∞), and its corresponding equilibrium distribution Ge(x)=μ∫0x P(S>y)dy are such that samples of them can be simulated. We further assume that G has a finite second moment. Our method involves the general method of dominated coupling from the past (DCFTP) and we use the single-server M/G/1 queue operating under the processor sharing discipline as an upper bound. Our algorithm yields the stationary distribution of the entire Kiefer–Wolfowitz workload process, the first coordinate of which is D. Extensions of the method to handle simulating generalized Jackson networks in stationarity are also remarked upon.

TheN×D-BMAP/G/1 Queueing Model: Queue Contents and Delay Analysis

We consider a single-server discrete-time queueing system with N sources, where each source is modelled as a correlated Markovian customer arrival process, and the customer service times are generally distributed. We focus on the analysis of the number of customers in the queue, the amount of work in the queue, and the customer delay. For each of these quantities, we will derive an expression for their steady-state probability generating function, and from these results, we derive closed-form expressions for key performance measures such as their mean value, variance, and tail distribution. A lot of emphasis is put on finding closed-form expressions for these quantities that reduce all numerical calculations to an absolute minimum.