Seungmo Kang

A Heuristic Approach to the Railroad Track Maintenance Scheduling Problem

Abstract: Every year, billions of dollars are spent on rail track maintenance to keep the serviceability of the railroad network. These maintenance projects (of different types) must be performed by suitable maintenance teams within a planning horizon. This article presents a time-space network model to solve the track maintenance scheduling problem (TMSP). The objective is to minimize the total travel costs of the maintenance teams as well as the impact of maintenance projects on railroad operation, which are formulated by three types of side constraints: mutually exclusive, time window, and precedence constraints. An iterative heuristic solution approach is proposed to solve the large-scale TMSP model with a large number of side constraints. The proposed model and solution approach are applied to a large-scale real-world problem. Compared to the current industry practice the model outcome eliminated all hard side-constraint violations and reduced the total objective value (travel costs and soft side-constraint violation penalties) by 66.8%.

Optimizing the Biofuels Infrastructure: Transportation Networks and Biorefinery Locations in Illinois

Growing biofuel mandates pose considerable challenges to the infrastructure needed across all stages of the supply chain − from crop production, feedstock harvesting, storage, transportation, and processing to biofuel distribution and use. This chapter focuses on the biofuel transportation and distribution network infrastructure, using Illinois as a case study. Building on an optimal land use allocation model for feedstock production, a mathematical programming model is used to determine optimal locations and capacities of biorefineries, delivery of bioenergy crops to biorefineries, and processing and distribution of ethanol and co-products (DDGS). The model aims to minimize total system costs in a multiyear planning horizon for the period of 2007–2022. Certain locations may be more suitable for corn and corn stover-based ethanol plants, others more for producing ethanol using perennial grasses (miscanthus)

The traveling purchaser problem with stochastic prices: Exact and approximate algorithms

The paper formulates an extension of the traveling purchaser problem where multiple types of commodities are sold at spatially distributed locations with stochastic prices (each following a known probability distribution). A purchasers goal is to find the optimal routing and purchasing strategies that minimize the expected total travel and purchasing costs needed to purchase one unit of each commodity. The purchaser reveals the actual commodity price at a seller upon arrival, and then either purchases the commodity at the offered price, or rejects the price and visits a next seller. In this paper, we propose an exact solution algorithm based on dynamic programming, an iterative approximate algorithm that yields bounds for the minimum total expected cost, and a greedy heuristic for fast solutions to large-scale applications. We analyze the characteristics of the problem and test the computational performance of the proposed algorithms. The numerical results show that the approximate and heuristic algorithms yield near-optimum strategies and very good estimates of the minimum total cost.

Evaluation of Pedestrian Safety: Pedestrian Crash Hot Spots and Risk Factors for Injury Severity

Pedestrian-involved crashes that occurred in the city of San Francisco, California, over 6 years from 2002 to 2007 were analyzed to evaluate two key aspects of pedestrian safety: occurrence and severity. This analysis was done to identify locations with frequent occurrences of pedestrian-involved crashes and to examine various risk factors for the injury severity of pedestrian-involved crashes. A geographical information system analysis for hot spot identification showed that the frequency of pedestrian crashes was greater in the vicinity of the central business district but that the crash rate (the number of crashes per walking trip) was higher in the periphery of the city. For injury analysis, an ordered probit model was specified to evaluate risk factors that increased the probability of severe injury and fatality. Those factors were age (<15 and ≥65), alcohol consumption, and cell phone use among pedestrian characteristics; nighttime, weekends, and rainy weather among environmental characteristics; and, among crash characteristics, the influence of alcohol, larger vehicles (pickups, buses, and trucks), and vehicles proceeding straight and striking a pedestrian. The methods discussed are readily applicable to the evaluation of safety performance in other regions where pedestrian crash data are available.

Location-based services: Enabling technologies and a concierge service model

It is widely believed that about 80 percent of public and private sectors’ day-to-day decisions are related to some sort of spatial and locational consideration, leaving only a few areas that are not affected by locational considerations. The Internet puts an unprecedented amount of locational information of all kinds at a user’s fingertips, information that can be used for personal production activities in a mind-boggling variety of ways (Ostensen, 2001). Location-based services (LBS) – sometimes called location-based mobile services (LBMS) – are an emerging technology combining information technology, Geographic Information Systems (GIS), positioning technology, Intelligent Transportation System (ITS) technology and the Internet. LBS combine hardware devices, wireless communication networks, geographic information and software applications that provide location-related guidance for customers (Kang, Oh and Kim, 2006). Location-based services differ from mobile position determination systems, such as Global Positioning Systems (GPS), in that they provide much broader, application-oriented location services, which become useful in specific situations, such as the following (Kim, 2004):

Heuristic algorithm for solving a multimodal location-based concierge service problem

As a location-based services problem, the concierge service problem is to find a minimum total cost for purchasing predetermined types and quantities of items with the shortest paths connecting the locations where the items are available. These locations are defined as points of interest (POIs). The total cost includes purchasing and stopping costs at POIs as well as the travel cost from origin to destination. To respond to a request for such a service, a search algorithm should be reasonably fast in computational time and high in accuracy. A heuristic search algorithm was developed by a Euclidean distance approach using a geographic information system. The algorithm was implemented with 1,248 POIs in the Seoul, South Korea, metropolitan area as a case study site. The road network is composed of 52,915 nodes and 77,339 links, and the existing subway network, and all existing bus routes were used for the implementation. Four scenarios were examined: a request for a service in peak and off-peak periods with and without turning restrictions. The results indicate that the computational time in each case is less than 4 s with the transit networks only and less than 30 s if the road network is used. The paper also evaluates the solutions generated from the algorithm.

Microwave Synthesis of Micro-Mesoporous Composite Material

Abstract Synthesis of micro-mesoporous composite material was attempted by using two different templates, [(CH 3 CH 2 CH 2 ) 4 NBr (TPABr) and C 14 H 29 (CH 3 ) 3 NBr (MTAB)] under the irradiation of microwave. Two precursor solutions for mesoporous and microporous phases were prepared using MTAB micelles and silicalite solution containing TPABr, respectively. The ratio of micro-mesophase was strongly influenced by the pretreatment conditions of silicalite-1 solution. To obtain composite materials having micro- and meso phases, nucleation step was needed for silicalite-1 solution prior to mixing with MTAB micelles. Microwave irradiation accelerated nucleation in pretreatment step and rapid crystallization. Synthetic process of these composite materials was monitored by TG-DTA and photoluminescence spectroscopy with pyrene probe. During the crystallization, the supramolecular interaction between MTA + micelles and SiO - /TPA + was observed and as the crystallization proceeds, the structure of composite materials changed from bimodal mesopore to multiple micro-mesopore.

Evaluating and addressing the effects of regression to the mean phenomenon in estimating collision frequencies on urban high collision concentration locations

Two different methods for addressing the regression to the mean phenomenon (RTM) were evaluated using empirical data: Data from 110 miles of freeway located in California were used to evaluate the performance of the EB and CRP methods in addressing RTM. CRP outperformed the EB method in estimating collision frequencies in selected high collision concentration locations (HCCLs). Findings indicate that the performance of the EB method can be markedly affected when SPF is biased, while the performance of CRP remains much less affected. The CRP method was more effective in addressing RTM.

Network Forensic Evidence Generation and Verification Scheme (NFEGVS)

One of the critical success factors of the cybercrime investigation is exact tracing back of hacker’s origin. However, criminals can easily modify or delete log files on victim machines. In addition, criminals can easily modify the source IP address so that network packet cannot be a strong evidence because it is easily spoofed. This study suggests a scheme for network forensic evidence generation and verification. This proposed scheme can show the attacker’s source location and guarantee the integrity of address fields. This scheme also can minimize the performance degradation of routers when generating forensic evidence via flow-based evidence traffic analysis.

Meta-heuristic approach for high-demand facility locations considering traffic congestion and greenhouse gas emission

AbstractLarge facilities in urban areas, such as storage facilities, distribution centers, schools, department stores, or public service centers, typically generate high volumes of accessing traffic, causing congestion and becoming major sources of greenhouse gas (GHG) emission. In conventional facility-location models, only facility construction costs and fixed transportation costs connecting customers and facilities are included, without consideration of traffic congestion and the subsequent GHG emission costs. This study proposes methods to find high-demand facility locations with incorporation of the traffic congestion and GHG emission costs incurred by both existing roadway traffic and facility users into the total cost. Tabu search and memetic algorithms were developed and tested with a conventional genetic algorithm in a variety of networks to solve the proposed mathematical model. A case study to determine the total number and locations of community service centers under multiple scenarios in Inch...