
Marcel MüllerOtto-von-Guericke University Magdeburg | OvGU · Institute of Logistics and Material Handling Systems
Marcel Müller
Master of Science
About
27
Publications
16,825
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354
Citations
Introduction
Marcel Müller is a research fellow at the Otto von Guericke University Magdeburg. He earned his master degree in Industrial Engineering for Logistics at the Otto von Guericke University Magdeburg. His research interests include modeling and simulation of logistics systems and handling of deadlocks.
Additional affiliations
February 2018 - June 2020
Education
April 2015 - December 2016
September 2014 - March 2015
October 2010 - August 2014
Publications
Publications (27)
Ongoing market concentration and a shortage of low-cost labor is compelling the German industrial laundry sector to adopt innovated automated solutions. RFID tags in textiles facilitate the use of automated systems. This paper introduces a new approach to picking and storing clean laundry. We simulate the system at an early stage to detect potentia...
When planning logistics systems with multiple transport objects or systems, modeling requires the implementation of complex control logic to avoid collisions and deadlocks. This paper illustrates a procedure for the development of such control logic on the example of rail-based storage and retrieval units in combinations with lifts in the picking a...
Automated guided vehicles (AGVs) form a large and important part of logistic systems to improve productivity and reduce costs. When multiple AGVs are running in limited and uncertain environments, lots of issues can occur, such as collisions and deadlocks, which need to be addressed. This paper presents a flexible simulation model for a warehouse w...
The planning of complex logistic systems must ensure collision- and deadlock-free operation of the logistic
system. Problem-specific rule-based algorithms used so far are inflexible with respect to infrastructure
changes and scale poorly with systems that grow larger. This paper shows a first approach to handle
logistic deadlocks with machine learn...
This paper introduces a modular simulation testbed developed for decision support in logistics and urban planning within the tourism sector, specifically applied to Şanlıurfa, Turkey, as part of the GeostaloVR project. The testbed integrates tourism value chains, urban development processes, and mobility flows to facilitate scenario testing and eva...
Due to pressing challenges such as high market volatility, complex global logistics, geopolitical turmoil and environmental sustainability, compounded by radical events such as the COVID-19 pandemic , the complexity of supply chain management has reached unprecedented levels. Together with increasing data availability and computing power, machine l...
Decision-making in supply chains is challenged by high complexity, a combination of continuous and discrete processes, integrated and interdependent operations, dynamics, and adaptability. The rapidly increasing data availability, computing power and intelligent algorithms unveil new potentials in adaptive data-driven decision-making. Reinforcement...
This paper aim is to provide a decision support model to assist the invoice delivery for about 200 customers in a law firm in Bogotá, Colombia. Each customer has a service time and establishes the conditions for the delivery, i.e., day, place, and time window. Invoices are delivered by motorcycle. We collect and analyze real travel and service time...
The paper presents a simulation case study dealing with a medium-sized company in the steel manufacturing industry. The production system of the company processes steel panels and profiles on two machines that are supplied with multiple roller conveyors and portal cranes. A special challenge is the partial return of raw material after processing th...
Deadlock handling is an important task when planning automated guided vehicle systems. The selection of the right strategy approach has a major impact on logistical figures. This paper presents the results of a simulation model for a comparison of the three typical deadlock handling strategies prevention, avoidance, and detection & resolution for a...
The article investigates the application of NeuroEvolution of Augmenting Topologies (NEAT) to generate and parameterize artificial neural networks (ANN) on determining allocation and sequencing decisions in a two-stage hybrid flow shop scheduling environment with family setup times. NEAT is a machine-learning and neural architecture search algorith...
Discrete-event simulation is an established method to support decision making for planning tasks in production and logistics. However, there are still many enterprises, especially smaller companies that do not use discrete-event simulation because of the high costs associated with buying and maintaining commercial simulation tools. The question is...
The integration of material flow simulation and digital planning solutions raises new challenges for the methodology and technical implementation of simulation models. The paper describes the use of a material flow simulation, which is controlling an AGV and interacting with digital twins of manufacturing cells. The digital twins determine the exac...
The following paper presents the application of Deep Q-Networks (DQN) for solving a flexible job shop problem with integrated process planning. DQN is a deep reinforcement learning algorithm, which aims to train an agent to perform a specific task. In particular, we train two DQN agents in connection with a discrete-event simulation model of the pr...
The paper proposes a simulation-based hyperheuristics approach to generate schedules for a two-stage hybrid flow shop scheduling problem with sequence-dependent setup times. The scheduling problem is derived from a company that is assembling printed circuit boards. A genetic algorithm determines sequences of standard dispatching rules that are eval...
The transport sector leads to detrimental effects on the economy, environment, and citizens quality of life. During recent years, some key performance indicators have been proposed to quantify these negative impacts on the economic, environmental, and social dimensions of the sustainability concept. We present a working paper that takes into accoun...
The paper shows how assigning different predefined dispatching rules for a predefined number of times at any points in time using a genetic algorithm can solve a hybrid flow shop scheduling problem with sequence-dependent setup times, using the example of a company producing printed circuit boards. The paper describes the implementation of the gene...
This paper describes the implementation of reference models for the application of a simulation model to various logistic processes in industrial laundries. The objective is to reduce the modeling effort for new applications significantly. The paper also provides industry-specific conceptual models, system descriptions and gives information about v...
Resumen: Los procesos en lavanderías industriales enfrentan una presión por aumentar su eficiencia debido a una concentración constante en el mercado. La industria de la lavandería en Alemania reporta un crecimiento constante en las ventas; según la asociación comercial "WIRTEX", las ventas totales de la industria de servicios textiles en Alemania...
Simulation models are still often only part for decision support in the planning area. For short-term decisions at the operational level, there have been good fundamentals since the 1990s, but still relatively few implementations, especially in the logistics sector. Our approach is to use real-time data to provide short-term forecasts, by using a s...
Industrial laundries in Germany face a high pressure to increase their efficiency due to an ongoing market concentration. While many processes in an industrial laundry are already highly automated and optimized, order picking is still done manually. As RFID proliferates in industrial laundries, goods become traceable and identifiable. This enables...
The planning of logistics systems is a complex task with important decisions to make. Simulation models can help already in the early planning process of these systems. Usually they only provide a visualization of the different planned concepts but with modern genetic algorithm it is possible to provide even more support. Numerous parameters are no...
Insufficient basic data, increasingly complex customer and product structures and a lack of transparency in the process structure increase the amount of laundry items in circulation, reduce machine utilization, delay deliveries and increase the error frequency. Competition is making it essential for laundries to operate quickly, reliably and cost e...
Digitization and the term Industry 4.0 are widespread topics. Several approaches already exist to determine the maturity of digitization in SMEs. But in addition to the considered production in the industry, logistics as a cross-section function can and should also be considered. The digitization of logistics in companies has similar challenges as...