Introduction to the Minitrack on GIS, Industry 4.0, and Sustainability

2023 | HICSS | Citations: 0

Authors: Shin, Namchul; Farkas, Daniel

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Methods: spatial analysis vehicle routing problem geographic analytics

A prescriptive analytics framework for efficient E-commerce order delivery

2021 | Decision Support Systems | Citations: 0

Authors: Kandula, Shanthan; Krishnamoorthy, Srikumar; Roy, Debjit

Abstract: Achieving timely last-mile order delivery is often the most challenging part of ... Expand

Abstract: Achieving timely last-mile order delivery is often the most challenging part of an e-commerce order fulfillment. Effective management of last-mile operations can result in significant cost savings and lead to increased customer satisfaction. Currently, due to the lack of customer availability information, the schedules followed by delivery agents are optimized for the shortest tour distance. Therefore, orders are not delivered in customer-preferred time periods resulting in missed deliveries. Missed deliveries are undesirable since they incur additional costs. In this paper, we propose a decision support framework that is intended to improve delivery success rates while reducing delivery costs. Our framework generates delivery schedules by predicting the appropriate delivery time periods for order delivery. In particular, the proposed framework works in two stages. In the first stage, order delivery success for every order throughout the delivery shift is predicted using machine learning models. The predictions are used as an input for the optimization scheme, which generates delivery schedules in the second stage. The proposed framework is evaluated on two real-world datasets collected from a large e-commerce platform. The results indicate the effectiveness of the decision support framework in enabling savings of up to 10.2% in delivery costs when compared to the current industry practice. Collapse

Topics: decision support electronic commerce geographic information system logistics management decision support system

Methods: machine learning XGBoost simulation random forest classification computational algorithm

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

A decision support framework for home health care transportation with simultaneous multi-vehicle routing and staff scheduling synchronization

2020 | Decision Support Systems | Citations: 0

Authors: Nasir, Jamal Abdul; Kuo, Yong-Hong

Abstract: Due to the ageing population and the prevalence of chronic diseases, Home Health ... Expand

Abstract: Due to the ageing population and the prevalence of chronic diseases, Home Health Care (HHC) practices are significantly increasing in developed countries to provide coordinated health related services to patients at their homes. Accordingly, the scope of HHC services is also expanding from typical nursing and postoperative care at home to cover all types of needs of elderly patients (e.g., personal care, drug delivery and meal services). This paper aims to address the pressing demand for HHC services and develop a novel and effective mathematical model and solution methodology for supporting health care service delivery decisions. Our decision support framework captures the real needs of HHC services, including the challenges of creating simultaneous schedules and route plans for a set of HHC staff and Home Delivery Vehicles (HDVs) under the requirements of syn­ chronization between HHC staff and HDVs visits, multiple visits to patients, multiple routes of HDVs and pickup/ delivery visits related precedence for HDVs. A Mixed Integer Linear Programming (MILP) model is developed to characterize the optimization problem. Considering the computational complexity of the problem, a Hybrid Genetic Algorithm (HGA) is proposed to suggest HHC planning decisions. The model formulation and proposed HGA are examined on real-life instances for demonstrating its practicality and randomly generated test instances for assessing the scalability of the proposed approach. The results show the effectiveness and efficiency of our solution methodology. Experimental results indicate that the proposed algorithm provided a good performance even with an increasing number of required synchronized services, whereas the heuristic tactics facilitate the HGA to produce better-quality solutions in a significantly shorter time. Our framework is expected to contribute to an important aspect of shared healthcare mobility. Collapse

Topics: Google+ application programming interface decision support

Methods: experiment mathematical model computational algorithm case study descriptive statistic

Autonomous Unmanned Ground Vehicles for Urban Logistics: Optimization of Last Mile Delivery Operations

2019 | HICSS | Citations: 0

Authors: Sonneberg, Marc-Oliver; Leyerer, Max; Kleinschmidt, Agathe; Knigge, Florian; Breitner, Michael H

Abstract: In an era dominated by ongoing urbanization and rising e-commerce, the efficient ... Expand

Abstract: In an era dominated by ongoing urbanization and rising e-commerce, the efficient delivery of goods within cities becomes a major challenge. As a new element of urban logistics, we discuss the potential of autonomous unmanned ground vehicles (AUGV) regarding the last mile delivery of shipments to customers. We propose an optimization model to minimize the delivery costs of urban shipments using AUGV. Simultaneously, best locations from a set of existing stations are selected for AUGV positioning and optimal route determination. With our developed Location Routing Problem, we provide decision support for parcel service providers, city authorities, and other relevant decision makers. Regarding the Green Information Systems domain, we tackle the lack of solution-oriented research addressing a more sustainable and locally emission free supply of goods within urban areas. Collapse

Topics: logistics management robotic green IS decision support environmental sustainability

Methods: optimization model case study operations research design science design process

Adaptive State Space Partitioning for Dynamic Decision Processes

2019 | Business & Information Systems Engineering | Citations: 0

Authors: Soeffker, Ninja; Ulmer, Marlin W.; Mattfeld, Dirk C.

Abstract: With the rise of new business processes that require real-time decision making, ... Expand

Abstract: With the rise of new business processes that require real-time decision making, anticipatory decision making becomes necessary to use the available resources wisely. Dynamic real-time problems occur in many business fields, for example in vehicle routing applications with stochastic customer service requests expecting a fast response. For anticipatory decision making, offline simulation-based optimization methods like value function approximation are promising solution approaches. However, these methods require a suitable approximation architecture to store the value information for the problem states. In this paper, an approach is proposed that finds and adapts this architecture iteratively during the approximation process. A computational proof of concept is presented for a dynamic vehicle routing problem. In comparison to conventional architectures, the proposed method is able to improve the solution quality and reduces the required architecture size significantly. Collapse

Topics: decision making business process management

Methods: simulation cluster analysis computational algorithm design artifact vehicle routing problem

Decision Support for Urban E-Grocery Operations

2018 | Americas Conference on Information Systems | Citations: 0

Authors: Leyerer, Max; Sonneberg, Marc-Oliver; Breitner, Michael H

Abstract: We discuss an alternative logistics concept for e-grocery operations using an ur ... Expand

Abstract: We discuss an alternative logistics concept for e-grocery operations using an urban network of refrigerated grocery lockers. Regarding the last mile delivery of food and other fast-moving consumer goods, customers either collect their orders by themselves or the products are delivered by means of electric cargo bicycles. To determine the optimal grocery locker locations and both, the routes from the lockers to the consumers as well as the routes from the depot to the grocery lockers, we propose a 2-echelon optimization model minimizing total costs. We present a Location Routing Problem (LRP) in combination with a customized Vehicle Routing Problem (VRP). With our decision support system (DSS), we react to the call of Malhotra et al. (2013) and Gholami et al. (2016) and address the lack of solution-oriented research. We contribute to the Green IS domain by extending the concept of e-grocery with an environmental and social component. Collapse

Topics: decision support system green IS logistics management application programming interface Microsoft Windows

Methods: optimization model vehicle routing problem

On the Value and Challenge of Real-Time Information in Dynamic Dispatching of Service Vehicles

2017 | Business & Information Systems Engineering | Citations: 0

Authors: Ulmer, Marlin W.; Heilig, Leonard; Voß, Stefan

Abstract: Ubiquitous computing technologies and information systems pave the way for real ... Expand

Abstract: Ubiquitous computing technologies and information systems pave the way for real-time planning and management. In the process of dynamic vehicle dispatching, the adherent challenge is to develop decision support systems using real-time information in an appropriate quality and at the right moment in order to improve their value creation. As real-time information enables replanning at any point in time, the question arises when replanning should be triggered. Frequent replanning may lead to efficient routing decisions due to vehicles' diversions from current routes while less frequent replanning may enable effective assignments due to gained information. In this paper, the authors analyze and quantify the impact of the three main triggers from the literature, exogenous customer requests, endogenous vehicle statuses, and replanning in fixed intervals, for a dynamic vehicle routing problem with stochastic service requests. To this end, the authors generalize the Markov-model of an established dynamic routing problem and embed the different replanning triggers in an existing anticipatory assignment and routing policy. They particularly analyze under which conditions each trigger is advantageous. The results indicate that fixed interval triggers are inferior and dispatchers should focus either on the exogenous customer process or the endogenous vehicle process. It is further shown that the exogenous trigger is advantageous for widely spread customers with long travel durations and few dynamic requests while the endogenous trigger performs best for many dynamic requests and when customers are accumulated in clusters. Collapse

Topics: decision making business process management Java

Methods: simulation business process model and notation modeling language Markov decision process vehicle routing problem

A decision support system tool for the transportation by barge of import containers: A case study

2015 | Decision Support Systems | Citations: 4

Authors: Fazi, Stefano; Fransoo, Jan C.; Van Woensel, Tom

Abstract: In this paper, we present a DSS that generates schedules for the transportation ... Expand

Abstract: In this paper, we present a DSS that generates schedules for the transportation of containers by barge in the hinterland, in particular from sea terminals to an inland terminal. As a case study, we propose the transportation from the ports of Rotterdam and Antwerp to a terminal in the south of the Netherlands, where the problem is typical. This problem is modeled as a heterogeneous fleet vehicle routing problem. The main decision is based on the trade-off of either consolidating containers to generate economies of scale with barges or alternatively dispatch, expensively and quickly, single containers by truck. The DSS is flexible as it can be applied to different settings by properly tuning the several parameters in the model. With numerical experiments, based on real world data, we evaluate the effectiveness of this system and its applicability. Collapse

Topics: decision support system random-access memory economies of scale logistics management decision making

Methods: computational algorithm experiment case study descriptive statistic qualitative interview

Multi-objective Analysis of Approaches to Dynamic Routing of a Vehicle

2015 | European Conference On Information Systems | Citations: 0

Authors: Grimme, Christian; Meisel, Stephan; Trautmann, Heike; Rudolph, Guenter; Wölck, Martin

Abstract: We consider a routing problem for a single vehicle serving customer locations in ... Expand

Abstract: We consider a routing problem for a single vehicle serving customer locations in the course of time. A subset of these customers must necessarily be served, while the complement of this subset contains dynamic customers which request for service over time, and which do not necessarily need to be served. The decision maker’s conflicting goals are serving as many customers as possible as well as minimizing total travel distance. We solve this bi-objective problem with an evolutionary multi-objective algorithm in order to provide an a-posteriori evaluation tool for enabling decision makers to assess the single-objective solution strategies that they actually use in real-time. We present the modifications to be applied to the evolutionary multi-objective algorithm NSGA2 in order to solve the routing problem, we describe a number of real-time single-objective solution strategies, and we finally use the gained efficient trade-off solutions of NSGA2 to exemplarily evaluate the real-time strategies. Our results show that the evolutionary multi-objective approach is well-suited to generate benchmarks for assessing dynamic heuristic strategies. Our findings point into future directions for designing dynamic multi-objective approaches for the vehicle routing problem with time windows. Collapse

Topics: decision support

Methods: computational algorithm experiment vehicle routing problem