Designing new models and algorithms to improve order picking operations

Order picking has been identified as a crucial factor for the competitiveness of a supply chain because inadequate order picking performance causes customer dissatisfaction and high costs. This dissertation aims at designing new models and algorithms to improve order picking operations and to support managerial decisions on facing current challenges in order picking. First, we study the standard order batching problem (OBP) to optimize the batching of customer orders with the objective of minimizing the total length of order picking tours. We present a mathematical model formulation of the problem and develop a hybrid solution approach of an adaptive large neighborhood search and a tabu search method. In numerical studies, we conduct an extensive comparison of our method to all previously published OBP methods that used standard benchmark sets to investigate their performance. Our hybrid outperforms all comparison methods with respect to average solution quality and runtime. Compared to the state-of-the-art, the hybrid shows the clearest advantages on the larger instances of the existing benchmark sets, which assume a larger number of customer orders and larger capacities of the picking device. Finally, our method is able to solve newly generated large-scale instances with up to 600 customer orders and six items per customer order with reasonable runtimes and convincing scaling behavior and robustness. Next, we address a problem based on a practical case, which is inspired by a warehouse of a German manufacturer of household products. In this warehouse, heavy items are not allowed to be placed on top of light items during picking to prevent damage to the light items. Currently, the case company determines the sequence for retrieving the items from their storage locations by applying a simple S-shape strategy that neglects this precedence constraint. As a result, order pickers place the collected items next to each other in plastic boxes and sort the items respecting the precedence constraint at the end of the order picking process. To avoid this sorting, we propose a picker routing strategy that incorporates the precedence constraint by picking heavy items before light items, and we develop an exact solution method to evaluate the strategy. We assess the performance of our strategy on a dataset provided to us by the manufacturer. We compare our strategy to the strategy used in the warehouse of the case company, and to an exact picker routing approach that does not consider the given precedence constraint. The results clearly demonstrate the convincing performance of our strategy even if we compare our strategy to the exact solution method that neglects the precedence constraint. Last, we investigate a new order picking problem, in which human order pickers of the traditional picker-to-parts setup are supported by automated guided vehicles (AGVs). We introduce two mathematical model formulations of the problem, and we develop a heuristic to solve the NP-hard problem. In numerical studies, we assess the solution quality of the heuristic in comparison to optimal solutions. The results demonstrate the ability of the heuristic in finding high-quality solutions within a negligible computation time. We conduct several computational experiments to investigate the effect of different numbers of AGVs and different traveling and walking speed ratios between AGVs and order pickers on the average total tardiness. The results of our experiments indicate that by adding (or removing) AGVs or by increasing (or decreasing) the AGV speed to adapt to different workloads, a large number of customer orders can be completed until the respective due date

Problemas de localização-distribuição de serviços semiobnóxios: aproximações e apoio à decisão

Doutoramento em Gestão IndustrialA presente tese resulta de um trabalho de investigação cujo objectivo se centrou no problema de localização-distribuição (PLD) que pretende abordar, de forma integrada, duas actividades logísticas intimamente relacionadas: a localização de equipamentos e a distribuição de produtos. O PLD, nomeadamente a sua modelação matemática, tem sido estudado na literatura, dando origem a diversas aproximações que resultam de diferentes cenários reais. Importa portanto agrupar as diferentes variantes por forma a facilitar e potenciar a sua investigação. Após fazer uma revisão e propor uma taxonomia dos modelos de localização-distribuição, este trabalho foca-se na resolução de alguns modelos considerados como mais representativos. É feita assim a análise de dois dos PLDs mais básicos (os problema capacitados com procura nos nós e nos arcos), sendo apresentadas, para ambos, propostas de resolução. Posteriormente, é abordada a localização-distribuição de serviços semiobnóxios. Este tipo de serviços, ainda que seja necessário e indispensável para o público em geral, dada a sua natureza, exerce um efeito desagradável sobre as comunidades contíguas. Assim, aos critérios tipicamente utilizados na tomada de decisão sobre a localização destes serviços (habitualmente a minimização de custo) é necessário adicionar preocupações que reflectem a manutenção da qualidade de vida das regiões que sofrem o impacto do resultado da referida decisão. A abordagem da localização-distribuição de serviços semiobnóxios requer portanto uma análise multi-objectivo. Esta análise pode ser feita com recurso a dois métodos distintos: não interactivos e interactivos. Ambos são abordados nesta tese, com novas propostas, sendo o método interactivo proposto aplicável a outros problemas de programação inteira mista multi-objectivo. Por último, é desenvolvida uma ferramenta de apoio à decisão para os problemas abordados nesta tese, sendo apresentada a metodologia adoptada e as suas principais funcionalidades. A ferramenta desenvolvida tem grandes preocupações com a interface de utilizador, visto ser direccionada para decisores que tipicamente não têm conhecimentos sobre os modelos matemáticos subjacentes a este tipo de problemas.This thesis main objective is to address the location-routing problem (LRP) which intends to tackle, using an integrated approach, two highly related logistics activities: the location of facilities and the distribution of materials. The LRP, namely its mathematical formulation, has been studied in the literature, and several approaches have emerged, corresponding to different real-world scenarios. Therefore, it is important to identify and group the different LRP variants, in order to segment current research and foster future studies. After presenting a review and a taxonomy of location-routing models, the following research focuses on solving some of its variants. Thus, a study of two of the most basic LRPs (capacitated problems with demand either on the nodes or on the arcs) is performed, and new approaches are presented. Afterwards, the location-routing of semi-obnoxious facilities is addressed. These are facilities that, although providing useful and indispensible services, given their nature, bring about an undesirable effect to adjacent communities. Consequently, to the usual objectives when considering their location (cost minimization), new ones must be added that are able to reflect concerns regarding the quality of life of the communities impacted by the outcome of these decisions. The location-routing of semi-obnoxious facilities therefore requires to be analysed using multi-objective approaches, which can be of two types: noninteractive or interactive. Both are discussed and new methods proposed in this thesis; the proposed interactive method is suitable to other multi-objective mixed integer programming problems. Finally, a newly developed decision-support tool to address the LRP is presented (being the adopted methodology discussed, and its main functionalities shown). This tool has great concerns regarding the user interface, as it is directed at decision makers who typically don’t have specific knowledge of the underlying models of this type of problems

Considering stakeholders’ preferences for scheduling slots in capacity constrained airports

Airport slot scheduling has attracted the attention of researchers as a capacity management tool at congested airports. Recent research work has employed multi-objective approaches for scheduling slots at coordinated airports. However, the central question on how to select a commonly accepted airport schedule remains. The various participating stakeholders may have multiple and sometimes conflicting objectives stemming from their decision-making needs. This complex decision environment renders the identification of a commonly accepted solution rather difficult. In this presentation, we propose a multi-criteria decision-making technique that incorporates the priorities and preferences of the stakeholders in order to determine the best compromise solution

Distributed Ledger Technology (DLT) Applications in Payment, Clearing, and Settlement Systems:A Study of Blockchain-Based Payment Barriers and Potential Solutions, and DLT Application in Central Bank Payment System Functions

Payment, clearing, and settlement systems are essential components of the financial markets and exert considerable influence on the overall economy. While there have been considerable technological advancements in payment systems, the conventional systems still depend on centralized architecture, with inherent limitations and risks. The emergence of Distributed ledger technology (DLT) is being regarded as a potential solution to transform payment and settlement processes and address certain challenges posed by the centralized architecture of traditional payment systems (Bank for International Settlements, 2017). While proof-of-concept projects have demonstrated the technical feasibility of DLT, significant barriers still hinder its adoption and implementation. The overarching objective of this thesis is to contribute to the developing area of DLT application in payment, clearing and settlement systems, which is still in its initial stages of applications development and lacks a substantial body of scholarly literature and empirical research. This is achieved by identifying the socio-technical barriers to adoption and diffusion of blockchain-based payment systems and the solutions proposed to address them. Furthermore, the thesis examines and classifies various applications of DLT in central bank payment system functions, offering valuable insights into the motivations, DLT platforms used, and consensus algorithms for applicable use cases. To achieve these objectives, the methodology employed involved a systematic literature review (SLR) of academic literature on blockchain-based payment systems. Furthermore, we utilized a thematic analysis approach to examine data collected from various sources regarding the use of DLT applications in central bank payment system functions, such as central bank white papers, industry reports, and policy documents. The study's findings on blockchain-based payment systems barriers and proposed solutions; challenge the prevailing emphasis on technological and regulatory barriers in the literature and industry discourse regarding the adoption and implementation of blockchain-based payment systems. It highlights the importance of considering the broader socio-technical context and identifying barriers across all five dimensions of the social technical framework, including technological, infrastructural, user practices/market, regulatory, and cultural dimensions. Furthermore, the research identified seven DLT applications in central bank payment system functions. These are grouped into three overarching themes: central banks' operational responsibilities in payment and settlement systems, issuance of central bank digital money, and regulatory oversight/supervisory functions, along with other ancillary functions. Each of these applications has unique motivations or value proposition, which is the underlying reason for utilizing in that particular use case

Robust Multi-Scenario Optimization of an Air Expeditionary Force Structure Applying Scatter Search to the Combat Forces Assessment Model

Modern Times\u27 bring change in all areas of life. Even the rate of change has changed, and is still changing to increase it\u27s enormous speed even more. Newer and more challenging questions face the military analysts everyday putting a question mark at the end of their last answer. Recently, the question of how to structure a robust air force to meet the requirements of competing, uncertain future scenarios has been keeping them busy. The new world order does not tolerate only being able to respond to a single scenario anymore, which once was considered a hard problem. Who knows what comes next? In this thesis, we propose a robust optimization methodology to provide an answer to the multi-scenario optimization problem. The methodology employs a meta-heuristic, Scatter Search, to guide the search of the multi-scenario solution space obtained by the evaluations of CFAM, the model currently used to respond to single theater scenario objectives. A Visual Basi

A theory and model for the evolution of software services.

Software services are subject to constant change and variation. To control service development, a service developer needs to know why a change was made, what are its implications and whether the change is complete. Typically, service clients do not perceive the upgraded service immediately. As a consequence, service-based applications may fail on the service client side due to changes carried out during a provider service upgrade. In order to manage changes in a meaningful and effective manner service clients must therefore be considered when service changes are introduced at the service provider's side. Otherwise such changes will most certainly result in severe application disruption. Eliminating spurious results and inconsistencies that may occur due to uncontrolled changes is therefore a necessary condition for the ability of services to evolve gracefully, ensure service stability, and handle variability in their behavior. Towards this goal, this work presents a model and a theoretical framework for the compatible evolution of services based on well-founded theories and techniques from a number of disparate fields.

A Framework To Model Complex Systems Via Distributed Simulation: A Case Study Of The Virtual Test Bed Simulation System Using the High Level Architecture

As the size, complexity, and functionality of systems we need to model and simulate con-tinue to increase, benefits such as interoperability and reusability enabled by distributed discrete-event simulation are becoming extremely important in many disciplines, not only military but also many engineering disciplines such as distributed manufacturing, supply chain management, and enterprise engineering, etc. In this dissertation we propose a distributed simulation framework for the development of modeling and the simulation of complex systems. The framework is based on the interoperability of a simulation system enabled by distributed simulation and the gateways which enable Com-mercial Off-the-Shelf (COTS) simulation packages to interconnect to the distributed simulation engine. In the case study of modeling Virtual Test Bed (VTB), the framework has been designed as a distributed simulation to facilitate the integrated execution of different simulations, (shuttle process model, Monte Carlo model, Delay and Scrub Model) each of which is addressing differ-ent mission components as well as other non-simulation applications (Weather Expert System and Virtual Range). Although these models were developed independently and at various times, the original purposes have been seamlessly integrated, and interact with each other through Run-time Infrastructure (RTI) to simulate shuttle launch related processes. This study found that with the framework the defining properties of complex systems - interaction and emergence are realized and that the software life cycle models (including the spiral model and prototyping) can be used as metaphors to manage the complexity of modeling and simulation of the system. The system of systems (a complex system is intrinsically a system of systems ) continuously evolves to accomplish its goals, during the evolution subsystems co-ordinate with one another and adapt with environmental factors such as policies, requirements, and objectives. In the case study we first demonstrate how the legacy models developed in COTS simulation languages/packages and non-simulation tools can be integrated to address a compli-cated system of systems. We then describe the techniques that can be used to display the state of remote federates in a local federate in the High Level Architecture (HLA) based distributed simulation using COTS simulation packages

1993 Annual report on scientific programs: A broad research program on the sciences of complexity

This report provides a summary of many of the research projects completed by the Santa Fe Institute (SFI) during 1993. These research efforts continue to focus on two general areas: the study of, and search for, underlying scientific principles governing complex adaptive systems, and the exploration of new theories of computation that incorporate natural mechanisms of adaptation (mutation, genetics, evolution)