An Optimization Approach to the Ordering Phase of an Attended Home Delivery Service

Attended Home Delivery (AHD) systems are used whenever a supplying company offers online shopping services that require that customers must be present when their deliveries arrive. Therefore, the supplying company and the customer must both agree on a time window, which ideally is rather short, during which delivery is guaranteed. Typically, a capacitated Vehicle Routing Problem with Time Windows forms the underlying optimization problem of the AHD system. In this work, we consider an AHD system that runs the online grocery shopping service of an international grocery retailer. The ordering phase, during which customers place their orders through the web service, is the computationally most challenging part of the AHD system. The delivery schedule must be built dynamically as new orders are placed. We propose a solution approach that allows to (non-stochastically) determine which delivery time windows can be offered to potential customers. We split the computations of the ordering phase into four key steps. For performing these basic steps we suggest both a heuristic approach and a hybrid approach employing mixed-integer linear programs. In an experimental evaluation we demonstrate the efficiency of our approaches

Individually optimized commercial road transport: A decision support system for customizable routing problems

The Vehicle Routing Problem (VRP) in its manifold variants is widely discussed in scientific literature. We investigate related optimization models and solution methods to determine the state of research for vehicle routing attributes and their combinations. Most of these approaches are idealized and focus on single problem-tailored routing applications. Addressing this research gap, we present a customizable VRP for optimized road transportation embedded into a Decision Support System (DSS). It integrates various model attributes and handles a multitude of real-world routing problems. In the context of urban logistics, practitioners of different industries and researchers are assisted in efficient route planning that allows for minimizing driving distances and reducing vehicle emissions. Based on the design science research methodology, we evaluate the DSS with computational benchmarks and real-world simulations. Results indicate that our developed DSS can compete with problem-tailored algorithms. With our solution-oriented DSS as final artifact, we contribute to an enhanced economic and environmental sustainability in urban logistic applications

Integrating operations research into green logistics:A review

Logistical activities have a significant global environmental impact, necessitating the adoption of green logistics practices to mitigate environmental effects. The COVID-19 pandemic has further emphasized the urgency to address the environmental crisis. Operations research provides a means to balance environmental concerns and costs, thereby enhancing the management of logistical activities. This paper presents a comprehensive review of studies integrating operations research into green logistics. A systematic search was conducted in the Web of Science Core Collection database, covering papers published until June 3, 2023. Six keywords (green logistics OR sustainable logistics OR cleaner logistics OR green transportation OR sustainable transportation OR cleaner transportation) were used to identify relevant papers. The reviewed studies were categorized into five main research directions: Green waste logistics, the impact of costs on green logistics, the green routing problem, green transport network design, and emerging challenges in green logistics. The review concludes by outlining suggestions for further research that combines green logistics and operations research, with particular emphasis on investigating the long-term effects of the pandemic on this field.</p

Routing Optimization with Generalized Consistency Requirements

The consistent vehicle routing problem (ConVRP) aims to design synchronized routes on multiple days to serve a group of customers while minimizing the total travel cost. It stipulates that customers should be visited at roughly the same time (time consistency) by several familiar drivers (driver consistency). This paper generalizes the ConVRP for any level of driver consistency and additionally addresses route consistency, which means that each driver can traverse at most a certain proportion of different arcs of routes on planning days, which guarantees route familiarity. To solve this problem, we develop two set partitioning-based formulations, one based on routes and the other based on schedules. We investigate valid lower bounds on the linear relaxations of both of the formulations that are used to derive a subset of columns (routes and schedules); within the subset are columns of an optimal solution for each formulation. We then solve the reduced problem of either one of the formulations to achieve an optimal solution. Numerical results show that our exact method can effectively solve most of the medium-sized ConVRP instances in the literature and can also solve some newly generated instances involving up to 50 customers. Our exact solutions explore some managerial findings with respect to the adoption of consistency measures in practice. First, maintaining reasonably high levels of consistency requirements does not necessarily always lead to a substantial increase in cost. Second, a high level of time consistency can potentially be guaranteed by adopting a high level of driver consistency. Third, maintaining high levels of time consistency and driver consistency may lead to lower levels of route consistency

A PATH ENUMERATION REFORMULATION OF THE SCHEDULE MIXED INTEGER PROGRAM SUPPORTING EXPEDITIONARY ADVANCED BASE OPERATIONS.

The U.S. Marine Corps needs an accurate model for analyzing its logistical needs in support of Expeditionary Advanced Base Operations (EABO). EABO is a doctrinal method used by the U.S. Navy and Marine Corps for denying adversary forces access to the maritime global commons. Deployment and sustainment of forces engaged in EABO requires a distribution network supported by various surface and airborne connector platforms of differing capacity and speed. The Marine Corps currently has a model for analyzing its distribution networks in support of EABO, the Schedule Mixed Integer Program (S-MIP). However, the computational difficulty of S-MIP limits its usefulness in large-scale experiments. This thesis describes a path enumeration-based reformulation known as the Path Enumeration Mixed-Integer Program (PE-MIP). PE-MIP is designed to provide a less computationally difficult model than the antecedent model S-MIP. We compare the runtime of PE-MIP and the quality of its solutions with that of S-MIP model and find that PE-MIP provides faster and superior results to S-MIP. The application of PE-MIP by the research sponsor will further inform current Marine Corps and Navy operational plans, acquisition, and force structure decisions.Operational Analysis Directorate, USMC, QUANTICO, VA, 22134Major, United States Marine CorpsApproved for public release. Distribution is unlimited

“Make no little plans”: Impactful research to solve the next generation of transportation problems

The transportation science research community has contributed to numerous practical and intellectual innovations and improvements over the last decades. Technological advancements have broadened and amplified the potential impacts of our field. At the same time, the world and its communities are facing greater and more serious challenges than ever before. In this paper, we call upon the transportation science research community to work on a research agenda that addresses some of the most important of these challenges. This agenda is guided by the sustainable development goals outlined by the United Nations and organized into three areas: (1) well-being, (2) infrastructure, and, (3) natural environment. For each area, we identify current and future challenges as well as research directions to address those challenges

AN INTERNET OF THINGS–BASED APPROACH TO INNOVATE CANTEEN STORES DEPARTMENT’S RETAIL OPERATIONS

In a competitive business environment, retail organizations in the Western world are capitalizing on technological tools and solutions to enhance customer experience and boost sales. Specifically, retailers that adopt Internet of Things (IoT) technologies improve customer experience and achieve cost savings. Yet such innovation is rare outside the Western world. Hence, early adopters of IoT technologies in retail operations in Pakistan could gain a competitive advantage. This study aims to create a deeper understanding of how Pakistan-based Canteen Stores Department (CSD), a retail chain mainly serving service members and their families, can use IoT technologies to significantly modernize and improve its operations and distinguish itself from competitors. To do so, this study conducts a qualitative analysis of scholarly articles on the relevant technologies and on IoT-based products offered by commercial companies. The authors also include findings from discussions with CSD customers and management. The results of the study indicate CSD can use IoT technologies to optimize store layout, offer interactive in-store mapping, automate checkout systems, implement smart shelving and digital price tagging, improve in-store promotions, enhance customer relationship management, and modernize distribution, transportation, and warehousing. The study also offers CSD management guidance on how to implement IoT technologies into retail operations at one location as a pilot.Outstanding ThesisLieutenant Commander, Pakistan NavyWing Commander, Pakistan Air ForceLieutenant Colonel, Pakistan ArmyApproved for public release. Distribution is unlimited