Hybrid order picking : A simulation model of a joint manual and autonomous order picking system

Order picking is a key process in supply chains and a determinant of business success in many industries. Order picking is still performed manually by human operators in most companies; however, there are also increasingly more technologies available to automate order picking processes or to support human order pickers. One concept that has not attracted much research attention so far is hybrid order picking where autonomous robots and human order pickers work together in warehouses within a shared workspace for a joint target. This study presents a simulation model that considers various system characteristics and parameters of hybrid order picking systems, such as picker blocking, to evaluate the performance of such systems. Our results show that hybrid order picking is generally capable of improving pure manual or automated order picking operations in terms of throughput and total costs. Based on the simulation results, promising future research potentials are discussed

An Empirical Warehouse Layout Design and Optimization Approach for Sri Lankan practitioners

Warehousing is a vital function for Sri Lanka, due to its trade-dependency. One of the most critical areas highlighted for development in Sri Lanka is infrastructure, of which warehouse holds a key bearing. This study will extend the theoretical framework of Warehouse Layout Designing published by Dissanayake and Rupasinghe, 2018 by incorporating viewpoints of the Sri Lankan practitioners. A focus group discussion with 5 prominent experts in the industry will be incorporated and extended questioner feedback from 10 other practitioners. This research focuses on bridging the theoretical gaps with respect to the warehouse design and optimization from the Sri Lankan context to fill the following research gaps. (1) Approach in identifying the practitioners and developing the questionnaire (2) Assess the warehouse designers approaches carried out by the practitioners (3) overall constraints within the industries in Sri Lanka

Trust in Sharing Resources in Logistics Collaboration

Collaboration on resource sharing advocates a joint usage of resources by multiple parties (actors) to attain mutual benefits. Resource sharing becomes vital when resources under consideration are scarce, challenging, and expensive to attain; as well when they are idle or underutilized. In collaborative logistics, resource sharing entails the joint usage of the physical and non-physical assets. Shared assets include the transportation vehicles (trucks), warehouses, distribution centers, information, on-demand staffing, and logistics services offered under cloud computing. Through sharing, collaborating partners in logistics can reduce costs and harms to the environment, but also improve the efficiency of logistical functions. Although collaborative sharing is beneficial, still many difficulties impede its uptake. The difficulties include how to choose partners, establish and maintain trust among partners involved. Indeed, in both academia and industry, low-level trust inhibits the collaboration critically on sharing logistics resources. To this end, the present dissertation addresses the trust problem encountered by collaborating partners when they are sharing logistics resources. It deals with the trust problem by developing the Trust Mechanism (TrustMech) concept. The primary role of the TrustMech is to help logistics stakeholders acquire the far-reaching understanding about the trustworthiness of prospective networks of sharing they configure, before advancing them to an implementation stage. The TrustMech stands on a mitigation approach that focuses on estimating outcomes of trust uncertainties a rather than a their sources. Henceforth, this dissertation advances on estimating outcomes of trust uncertainties to answer the following central Research Question (RQ): how can collaborating partners acquire the far-reaching understanding about the trustworthiness of prospective networks of sharing they configure? An approach to the research problem, which as well answers the RQ proceeds as follows. The first steps involve establishing behavioral factors and parameters, which influence trust in collaborative sharing of logistics resources. The second stage entails establishing a conceptual framework that depicts and guides trust-based interaction of collaborating partners. The third step comprises developing the TrustMech concept, validating it in both the conceptual and operational aspects, and demonstrating its application by carrying out controlled (simulation) experiments in Multi-Agent Systems. In particular, the proposed TrustMech concept characterizes fundamental logical processes that account for trusting decisions, actions, and reactions of collaborating partners to reinforce emergent trusting outcomes The core contributions of this dissertation are the general-purpose TrustMech and the operational TrustMech. The operational TrustMech is customary for collaborative sharing of logistics resources. Regarding its application, the operational TrustMech provides logistics managers and stakeholders the ability to forecast how a configured network of sharing may, in respect of trustworthiness, function upon its implementation. To clarify further, the operational TrustMech scrutinizes many issues. For example, it scrutinizes trustworthiness of the configured network regarding possible strengths and pitfalls and provides pathway explanations underlying such foreseen strengths and pitfalls. Secondly, the operational TrustMech scrutinizes effects which such strengths and pitfalls can generate. Moreover, the operational TrustMech estimates an extent to which behavioral factors influence the trustworthiness of the individual partner and entire resource sharing network. Future research works include extending the TrustMech and replicating the study using system data. Additional future work consists of adjusting the design and settings used, as well as incorporating additional predictor and response variables into the operational TrustMech

Physical internet-enabled hyperconnected distribution assessment

L'Internet Physique (IP) est une initiative qui identifie plusieurs symptômes d'inefficacité et non-durabilité des systèmes logistiques et les traite en proposant un nouveau paradigme appelé logistique hyperconnectée. Semblable à l'Internet Digital, qui relie des milliers de réseaux d'ordinateurs personnels et locaux, IP permettra de relier les systèmes logistiques fragmentés actuels. Le but principal étant d'améliorer la performance des systèmes logistiques des points de vue économique, environnemental et social. Se concentrant spécifiquement sur les systèmes de distribution, cette thèse remet en question l'ordre de magnitude du gain de performances en exploitant la distribution hyperconnectée habilitée par IP. Elle concerne également la caractérisation de la planification de la distribution hyperconnectée. Pour répondre à la première question, une approche de la recherche exploratoire basée sur la modélisation de l'optimisation est appliquée, où les systèmes de distribution actuels et potentiels sont modélisés. Ensuite, un ensemble d'échantillons d'affaires réalistes sont créé, et leurs performances économique et environnementale sont évaluées en ciblant de multiples performances sociales. Un cadre conceptuel de planification, incluant la modélisation mathématique est proposé pour l’aide à la prise de décision dans des systèmes de distribution hyperconnectée. Partant des résultats obtenus par notre étude, nous avons démontré qu’un gain substantiel peut être obtenu en migrant vers la distribution hyperconnectée. Nous avons également démontré que l'ampleur du gain varie en fonction des caractéristiques des activités et des performances sociales ciblées. Puisque l'Internet physique est un sujet nouveau, le Chapitre 1 présente brièvement l’IP et hyper connectivité. Le Chapitre 2 discute les fondements, l'objectif et la méthodologie de la recherche. Les défis relevés au cours de cette recherche sont décrits et le type de contributions visés est mis en évidence. Le Chapitre 3 présente les modèles d'optimisation. Influencés par les caractéristiques des systèmes de distribution actuels et potentiels, trois modèles fondés sur le système de distribution sont développés. Chapitre 4 traite la caractérisation des échantillons d’affaires ainsi que la modélisation et le calibrage des paramètres employés dans les modèles. Les résultats de la recherche exploratoire sont présentés au Chapitre 5. Le Chapitre 6 décrit le cadre conceptuel de planification de la distribution hyperconnectée. Le chapitre 7 résume le contenu de la thèse et met en évidence les contributions principales. En outre, il identifie les limites de la recherche et les avenues potentielles de recherches futures.The Physical Internet (PI) is an initiative that identifies several symptoms of logistics systems unsustainability and inefficiency and tackles them by proposing a novel paradigm called Hyperconnected Logistics. Similar to the Digital Internet, which connects thousands of personal and local computer networks, PI will connect the fragmented logistics systems of today. The main purpose is to enhance the performance of logistics systems from economic, environmental and social perspectives. Focusing specifically on the distribution system, this thesis questions the order of magnitude of the performance gain by exploiting the PI-enabled hyperconnected distribution. It is also concerned by the characterization of the hyperconnected distribution planning. To address the first question, an exploratory research approach based on optimization modeling is applied; first, the current and prospective distribution systems are modeled. Then, a set of realistic business samples are created, and their economic and environmental performance by targeting multiple social performances are assessed. A conceptual planning framework is proposed to support the decision making in the hyperconnected distribution system. Based on the results obtained by our investigation, it can be argued that a substantial gain can be achieved by shifting toward Hyperconnected Distribution. It is also revealed that the magnitude of the gain varies by business characteristics and the targeted social performance. Since the Physical Internet is a novel topic, chapter 1 briefly introduces PI and Hyperconnected Logistics. Chapter 2 discusses the research foundations, goal and methodology. It also describes the challenges of conducting this research and highlights the type of contributions aimed for. Chapter 3 presents the optimization models including a core distribution network design modeling approach. Influenced by the characteristics of the current and prospective distribution systems, three distribution system-driven models are developed. Chapter 4 engages with the characterization of the business samples, the modeling and calibration of the parameter that are employed in the models. The exploratory investigation results are presented in Chapter 5. Chapter 6 describes the hyperconnected distribution planning framework. Chapter 7 summarizes the content of the thesis and highlights the main contributions. Moreover, it identifies the research limitations and potential future research avenues

Agent-based material transportation scheduling of AGV systems and its manufacturing applications

制度:新 ; 報告番号:甲3743号 ; 学位の種類:博士(工学) ; 授与年月日:2012/9/10 ; 早大学位記番号:新6114Waseda Universit

Congestion based Truck Drone intermodal delivery optimization

Commerce companies have experienced a rise in the number of parcels that need to be delivered each day. The goal of this study is to provide a decision-making procedure to assist carriers in taking a more significant role in selecting cost and risk-efficient truck-drone intermodal delivery routing plan. The congestion-based model is developed to select the method of parcel delivery utilizing a truck and a drone for optimizing cost and time. A study also has been conducted to compare drone-only and truck-only delivery routing plan. The proposed A* Heuristic algorithm and the OSRM application generate the travel path for drone and a truck along with the time of travel. Case studies have been conducted by varying the weight provided to cost and risk variable, studies indicate that there is a significant change in drone delivery travel time and cost with increase of cost weightage

Order picking strategies for healthcare warehouses.

Order picking is the process of collecting goods and items in specified quantities from storage locations, in response to customer orders. Since many labor resources are involved in this process, finding ways to make it more efficient have been a primary goal for researchers and practitioners. Determining a better allocation of products to the storage areas, finding the best route and sequence to pick multiple products, and choosing the best picking policies to minimize congestion in the aisles are just a few of many objectives regarding order picking process. Due to regulatory compliances and the chance of product spoilage, additional criteria should be taken into account when dealing with order picking in a healthcare warehouse. Following the first-expired, first-out (FEFO) principle and fulfilling an order from a single manufacturing batch, are two of the requirements that are considered in this research. Moreover, minimizing the traveled distance to picking locations, minimizing the penalty or cost of using the space by depleting it quicker, and maximizing the probability of a successful pick in the future by considering the order size distribution are the other objectives that have been studied in this research. The desired order picking problem is formulated and solved as a multi-objective mixed integer programming optimization model. Assigning importance weights to each objective and obtaining one single solution does not provide a full picture of all possible and potentially attractive solutions. On the other hand, providing all the solutions is not always achievable as it is computationally expensive and most of the time a set of rules and regulations drive decision makers toward the chosen solution. Finally, this research focuses on solution simplicity, generality, and practicality since the solution will be implemented by order pickers. To achieve this goal, a novel approach using association rule mining is presented. Products are classified in different groups and some order picking rules are derived based on the relations of these classes together. These rules are then compared with the results of multi-objective optimization model to evaluate their quality. The comparison results showed that surprisingly, some simple rules extracted from the preferences of the decision maker, can obtain good quality solutions. For example, in products with high order variability, it is possible to generate solutions within an average gap of less than ±8.8% from the multi-objective optimization solutions. The findings of this research leads to the following primary recommendations: Orders should be picked based on the expiration dates of the batches (FEFO principle) unless, the amount of inventory in the location is exactly equal to the order amount. In that case, regardless of the expiration date and the traveled distance to the location, it is better to pick from that location and make the space available. If product replenishment is not instantaneous, regardless of the expiration date and the traveled distance to the location, it is recommended to not pick from a location which can lead to an undesired and low amount of inventory. Due to order variability of the product, it is better to wait until the inventory in that location transfers to a desirable level. If fast replenishment of products is obtainable, then prioritizing traveled distance over the objectives linked to space usage and inventory is advisable

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

Public-private perspectives on supply chains of essential goods in crisis management

Public authorities are responsible to maintain the population’s supply with essential goods like food or drugs at any time. Such goods are produced, transported and sold by companies in supply chains. Past supply crises all over the world have showcased numerous examples of spontaneous collaboration between public authorities and companies in supply chains. However, insights on formal collaboration which is agreed upon in the preparedness phase is rare in both practice and literature. Therefore, this dissertation’s first research objective is to identify under which circumstances companies are most willing to collaborate with public authorities. In this context, public authorities\u27 and companies\u27 characteristics, resources and roles in a collaboration are identified from literature research as well as real-life cases in Study A. Study B empirically determines companies\u27 preferred preconditions for collaboration: Companies value the continuity of their business processes and expect to be compensated monetarily or by lifted restrictions. The second research objective is to develop collaborative supply chain concepts and evaluate them from public and private perspectives. Study C develops a collaboration concept in a real-time setting in which commercial trucks are jointly re-routed into crisis regions. In Study D, public authorities coordinate tactical use of commercial last-mile delivery vehicles for the home supply with food and drugs. In Study E, strategic collaboration in using dual-use warehouses is investigated with a focus on logistics networks. Study F determines the impact of demand shortfalls and payment term extensions on financial and physical flows in food supply chains. In Studies C-F, the main drivers for effectiveness and efficiency are investigated. By examining collaboration between companies and public authorities in supply crises, this dissertation contributes to the research streams of supply chain risk management and so-called extreme supply chain management. The results provide public decision-makers with insights into companies\u27 motivation to engage in public crisis management. The developed collaborative supply chain concepts serve public authorities as a basis for collaboration design and companies as starting points for integrating public-private collaboration into their endeavors to make supply chains more resilient