Mahdieh Allahviranloo

Investment optimization on port’s development by fuzzy integer programming

Abstract In this research, the main purpose is to formulate a model to determine the optimum investment on port development from national investment prospective; on the other hand, costs and benefits are calculated from consumer and investor’s viewpoint. The formulated model is an integer-programming model. The emphasis is on how to formulate an investment optimization problem where cargo operation, investment costs, cargo-handling capacity, cargo transportation network, and the world maritime fleet constraints are included. Fuzzy numbers are used for cargo forecast study results. The output of the model is the type of design ships and design berths which are needed in each sub period, so that the port planner (the government) will find out the optimum development plan of port in each sub period when there is uncertainty in cargo handling forecast (fuzzy numbers).

Modeling the activity profiles of a population

ABSTRACT Chains of activities performed during the course of the day are interconnected such that participation in one activity and the time allocated to that specific activity correspondingly influence the time-use behavior of a traveler along the course of the day. This points to the importance of analyzing trajectories of patterns as a set of activities with such specific characteristics as start time, duration, and sequence, rather than simply analyzing participation in each activity singularly. In this paper we present a methodology to answer a main question in the trajectory analysis: How to generate activity patterns trajectories, and how to conduct useful analysis that eventually makes inferences drawn from the time-use behavior of individuals applicable to the population-at-large possible? The methodology presented in this paper can be applied to synthetize chains of activities and their space–time distribution. It starts with clustering the activity patterns into a small set of representative patterns by using message passing algorithms, and then capturing the correlation among demographic profiles of travelers to the bundles of activities performed and their corresponding time sequence using multivariate probit models. We apply the methodology to two sets of data: (1) California household travel survey data for year 2000–2001, and (2) California household travel survey data for year 2010–2011. The longitudinal analysis performed in this work: (1) proves the robustness of proposed methodology in replicating time-use behavior and synthetizing activity chains, (2) reveals dynamics of changes in the trajectories of activity patterns during a 10-year time span, and (3) quantifies the influence of different socio-demographic variables on the trajectories of activities performed by travelers by implementing a statistical analysis on the distribution of estimates.

Trade-offs among planned versus performed activity patterns

ABSTRACT This paper focuses on the development of a methodology to identify the latent factors leading to changes in the planned itineraries of travellers that result in their actual activity patterns. Specifically, we propose a way to utilise patterns of activities established by individuals across multiple days to generate possible alternative actions by these individuals when faced with conditions that produce a discrepancy between performed and planned patterns on a particular day. The choice alternatives, which are unobserved, are inferred by rules applied to comprehensive multiday data collected in Belgium, consisting of information regarding planned activity itineraries, performed activity/travel diaries, and demographics of travellers. These data are utilised to analyse and explore the underlying reasons preventing individuals from performing their planned activities on a given day, and to identify the influential parameters that lead individuals to trade their planned patterns with those actually performed. Using multiday data, we generate all possible combinations of categories of activities – mandatory, maintenance, discretionary, and pickup/drop off activities – that can form patterns for individuals. Under the assumption that the performed patterns have the closest utility to the planned patterns, we estimate the latent factors that influence travellers’ time use behaviour using a multinomial probit choice structure in which the covariance structure of the choice alternatives is specified in terms of the overlap in activities. We further identify the ‘costs’ associated with making changes in planned agenda (replacing, inserting, or deleting an activity). These penalty values are estimated using ‘Parallel Genetic Algorithm’, where the fitness function is the likelihood function estimated under the multinomial choice model structure. The results show that individuals’ mobility decisions related to mandatory activities are more robust than those associated with their non-mandatory counterparts.

Probabilistic Fleet Sizing and Routing Problem to Minimize Mobility Disparities

The objective of this paper is to develop an analytical model to analyze the mobility behavior of a target population and to minimize the disparities. The analysis is conducted using household travel survey data collected from 7993 residents of five boroughs of New York City, where citizens with mobility impairments are considered as our target population. The study starts by quantifying the existing gap in the patterns of the mobility-impaired individuals and the base population followed by the generation of new activities in the agenda of the target population using the patterns of their nearest neighbors in the base population. Activities are generated based on copula sampling method. Attributes of activities forming the new agenda of the target population are the inputs that will be used for the design of an optimum ridesharing system. By integrating probabilistic models with the existing routing models, we develop a methodology to identify the optimum fleet size, optimum route, and optimum schedule such that all requests of the physically impaired travelers are fulfilled within a reasonable wait time for ride requesters.