A Decision Framework to Recommend Cruising Locations for Taxi Drivers under the Constraint of Booking Information

2022 | ACM Transactions on Management Information Systems | Citations: 1

Authors: Hsieh, Hsun-Ping; Lin, Fandel; Chen, Nai-Yu; Yang, Tzu-Hsin

Abstract: As the demand for taxi reservation services has increased, increasing the income ... Expand

Abstract: As the demand for taxi reservation services has increased, increasing the income of taxi drivers with advanced services has attracted attention. In this article, we propose a path decision framework that considers real-time spatial-temporal predictions and traffic network information. The goal is to optimize a taxi driver's profit when considering a reservation. Our framework contains four components. First, we build a grid-based road network graph for modeling traffic network information for speeding up the search process. Next, we conduct two prediction modules that adopt advanced deep learning techniques to guide proper search directions for recommending cruising locations. One module of the taxi demand prediction is used to estimate the pick-up probabilities of passengers in the city. Another one is destination prediction, which can predict the distribution of drop-off probabilities and capture the flow of potential passengers. Finally, we propose the H* (Heuristic-star) algorithm, which jointly considers pick-up probabilities, drop-off distribution, road network, distance, and time factors based on the attentive heuristic function to dynamically recommend next cruising locations. Compared with existing route planning methods, the experimental results on a real-world dataset have shown that our proposed approach is more effective and robust. Moreover, our designed search scheme in H* can decrease the computing time and allow the search process to be more efficient. To the best of our knowledge, this is the first work that focuses on guiding a route, which can increase the income of taxi drivers under the constraint of booking information. Collapse

Topics: IT work ride sharing platform decision making

Methods: computational algorithm experiment cross sectional research longitudinal research time series analysis

Support Your Local: IS-Based Collaborative Delivery Service for Urban Communities

2020 | International Conference on Information Systems | Citations: 0

Authors: Greif, Toni; Stein, Nikolai; Flath, Christoph

Abstract: The vulnerabilities of small physical retail stores are nowadays greater than ev ... Expand

Abstract: The vulnerabilities of small physical retail stores are nowadays greater than ever. Competition in the retail sector has intensified with rapid digitalization, growing e-commerce retail and fast delivery services. Driven by the COVID-19 pandemic, there are serious concerns that this trend will persist in the future. To support local retailers during these challenging times, we cooperate with a local business initiative in Germany to develop a collaborative urban delivery system for the dispatch of goods. Thereby, we try to support both customers and local businesses to compensate for declining in-store sales. Additionally, we enable local cab services–that also face reduced demand–to use their idle capacity to deliver the goods. The design science research project is intended to offer a perspective beyond the pandemic. In the long term, the system should enable retailers to acquire new customers within the group of e-commerce shoppers. Since we want to involve as many parties as possible, regardless of their digital maturity, we use multiple communication channels. Collapse

Topics: usability user interface graphical user interface IS maturity information technology capability

Methods: vehicle routing problem design science travelling salesman problem computational algorithm design artifact

Integrating Data Collection Optimization into Pavement Management Systems

2017 | Business & Information Systems Engineering | Citations: 0

Authors: Bazi, Gabriel; El Khoury, John; Srour, F. Jordan

Abstract: This paper describes a method for using location data to optimize the routing of ... Expand

Abstract: This paper describes a method for using location data to optimize the routing of pavement data collection vehicles. In much of the developed world, pavement testing is performed on a regular basis; the pavement testing data, in turn, serves as input to Pavement Management Systems. Currently, in the United States of America, state departments of transportation plan this data collection work by providing the list of roads that must be tested and then leave the routing of the vehicles to the equipment operators who typically execute the work in an ad hoc manner. This study presents the processes required to code the list of roads for testing, select appropriate hotels in the region of testing, and apply a Traveling Salesman Problem with Hotel Stops model to derive a route. Applying the processes to a case study shows significant cost savings associated with this method of roadway testing, as opposed to the current ad hoc methods. Collapse

Topics: Google+ application programming interface geographic information system data integration IT work

Methods: case study optimization model mixed-integer programming literature study travelling salesman problem

The data quality improvement plan: deciding on choice and sequence of data quality improvements

2017 | Electronic Markets | Citations: 2

Authors: Kleindienst, Dominikus

Abstract: With the rapid growth in the amount of data generated worldwide, ensuring adequa ... Expand

Abstract: With the rapid growth in the amount of data generated worldwide, ensuring adequate data quality (DQ) is increasingly becoming a challenge for companies: data are, among others, required to be timely, complete, consistent, valid, and accessible. Given this multidimensionality, DQ improvements (DQIs) need to be purposefully chosen and –as there can be path dependencies– arranged in an optimal sequence. Thus, this research contributes to performing the complex multidimensional task of ensuring adequate DQ in an economically reasonable manner by providing a formal decision model for identifying an optimal data quality improvement plan (DQIP). This DQIP comprises both an economically reasonable selection and execution sequence of DQIs based on existing interrelationships between different DQ dimensions. Furthermore, a comprehensive Monte Carlo simulation provides insights in implications to put the decision model into operation. For practitioners, the decision model enables efficient allocation of resources to DQIs. The model also gives advice on how to sequence DQIs and attracts attention to the complex problem context of DQ in order to support valid managerial decisions. Collapse

Topics: data quality

Methods: Monte Carlo simulation simulation descriptive statistic travelling salesman problem knapsack problem

Retail Warehouse Loading Dock Coordination by Core-selecting Package Auctions

2015 | European Conference On Information Systems | Citations: 0

Authors: Karaenke, Paul; Bichler, Martin; Minner, Stefan

Abstract: Congestions at loading docks can cause severe delays in logistics processes and ... Expand

Abstract: Congestions at loading docks can cause severe delays in logistics processes and cause increasing bottlenecks for truck routes. For warehouses, uncoordinated arrivals of trucks make appropriate staffing difficult and congestions can interfere with other processes at the facility. To mitigate congestions at loading docks, we propose package auctions to allocate time slots to trucks. Collapse

Topics: price management logistics management information exchange

Methods: simulation computational algorithm design artifact experiment literature study

Theories: game theory

Evaluating Idle Time Policies for Real-Time Routing of a Service Vehicle

2015 | European Conference On Information Systems | Citations: 0

Authors: Meisel, Stephan; Woelck, Martin

Abstract: We empirically evaluate a number of alternative decision rules for real-time rou ... Expand

Abstract: We empirically evaluate a number of alternative decision rules for real-time routing of a service vehicle. The particular feature of the decision rules is that they aim at more efficient routing of the vehicle by deliberately introducing vehicle idle times. Our goal is to provide both routing information system providers and supply chain operators with criteria for application of these policies in practice. Collapse

Topics: supply chain management

Methods: experiment vehicle routing problem travelling salesman problem optimization model literature study

The Position-Aware-Market: Optimizing Freight Delivery for Less-Than-Truckload Transportation

2012 | Americas Conference on Information Systems | Citations: 0

Authors: Qiu, Xiaoqiu; Neumann, Dirk; Goetzinger, Markus

Abstract: The increasing competition faced by logistics carriers requires them to ship at ... Expand

Abstract: The increasing competition faced by logistics carriers requires them to ship at lower cost and higher efficiency. In reality, however, many trucks are running empty or with a partial load. Bridging such residual capacity with real time transportation demand enhances the efficiency of the carriers. We therefore introduce the Position-Aware-Market (PAM), where transportation requests are traded in real time to utilize transportation capacities optimally. In this paper we mainly focus on the decision support system for the truck driver, which solves a profit- maximizing Pickup and Delivery Problem with Time Windows (PM-PDPTW). We propose a novel Recursive Branch-and-Bound algorithm that solves the problem optimally, and apply it to a Tabu-Search heuristic for larger problem instances. Simulations show that problems with up to 50 requests can be solved optimally within seconds. Larger problems with 200 requests can be solved approximately by Tabu-Search in seconds, retaining 60% of the optimal profit. Collapse

Topics: decision support system

Methods: computational algorithm simulation optimization model travelling salesman problem mathematical model

A decision support system of vehicle routing and refueling for motor carriers with time-sensitive demands

2012 | Decision Support Systems | Citations: 0

Authors: Suzuki, Yoshinori

Abstract: Given the recent trend of raising fuel cost and the increased time-sensitiveness ... Expand

Abstract: Given the recent trend of raising fuel cost and the increased time-sensitiveness of shippers, an extensive pressure is placed on the motor-carrier industry to meet the time-constrained customer demands at minimum fuel cost. We propose a decision support system that allows motor carriers to route each vehicle such that the vehicle not only visits all the customers in time (without violating time windows), but also utilizes the “cheapest” gas stations (cheapest truck stops in the region) as refueling points during the tour. While this approach does not necessarily minimize a vehicle's fuel consumption, as it often suggests using non-shortest routes with cheap gas stations (truck stops), it allows the vehicle to reduce the unit cost of buying fuel. Computational testing shows that the proposed approach may attain up to 4.29% savings in fuel cost for motor carriers. Collapse

Topics: price management decision support system database system Visual Basic anonymity

Methods: computational algorithm experiment simulation statistical hypothesis test linear optimization

An Analytical Model to Evaluate Alternative Methods for Distance Calculation in GIS-Based Vehicle Routing Decision Support Systems

2003 | Americas Conference on Information Systems | Citations: 0

Authors: Ray, Julian

Abstract: Most commercial vehicle-routing decision support systems employ network optimiza ... Expand

Abstract: Most commercial vehicle-routing decision support systems employ network optimization methods for calculating inter-stop distances over digital street data. Although potentially more accurate, these optimization methods are computationally intensive, increase overall problem complexity and require more sophisticated and expensive GIS systems to support the functions. Alternative approaches for calculating inter-stop street distances have been re-emerging in the literature as software developers seek to increase efficiency when solving these types of complex problems allowing larger problems to be solved in real-time. This research in progress describes an analytical model to determine if approximation methods are comparable, in terms of the quality of solutions generated, to computationally expensive optimization methods which have been generally adopted by software vendors. Collapse

Topics: decision support system geographic information system

Methods: computational algorithm regression analysis method travelling salesman problem linear regression analysis optimization model

A Hueristic Learning Algorithm for Traveling Salesman Problems

2000 | Americas Conference on Information Systems | Citations: 0

Authors: Lau, Sim Kim; Shue, L Y

Abstract: This paper describes the development of a heuristic learning algorithm to solve ... Expand

Abstract: This paper describes the development of a heuristic learning algorithm to solve traveling salesman problems. The heuristic evaluation function of this algorithm considers both local and global estimated distance information. The heuristic learning mechanism allows the algorithm to update the heuristic estimates of visited states and hence modify the tour configuration along the search process. The search engine of the algorithm incorporates Delaunay Triangulations as part of the search strategy to identify candidate edges during the search process. Collapse

Methods: computational algorithm travelling salesman problem