Simulation based case studies in logistics education and applied research pdf

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simulation based case studies in logistics education and applied research pdf

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Simulation-based Case Studies in Logistics presents an intensive learning course on the application of simulation as a decision support tool to tackle complex logistic problems. The book describes and illustrates different approaches to developingMoreSimulation-based Case Studies in Logistics presents an intensive learning course on the application of simulation as a decision support tool to tackle complex logistic problems.

This paper introduces a practical approach for the comprehensive simulation based planning and optimization of the production and logistics of a discrete goods manufacturer. Although simulation and optimization are well-established planning aides in production and logistics, their actual application in the field is still scarce, especially in small and medium-sized enterprises SMEs. This is largely due to the complexity of the planning task and lack of practically applicable approaches for real-life planning scenarios. This paper provides a case study from the food industry, featuring a comprehensive planning approach based on simulation and optimization.

Transportation Research Part E: Logistics and Transportation Review

This paper introduces a practical approach for the comprehensive simulation based planning and optimization of the production and logistics of a discrete goods manufacturer. Although simulation and optimization are well-established planning aides in production and logistics, their actual application in the field is still scarce, especially in small and medium-sized enterprises SMEs. This is largely due to the complexity of the planning task and lack of practically applicable approaches for real-life planning scenarios.

This paper provides a case study from the food industry, featuring a comprehensive planning approach based on simulation and optimization. The approach utilizes an offline-coupled multilevel simulation to smooth production and logistics planning via optimization, to optimally configure the production system using discrete-event simulation and to optimize the logistics network utilizing an agent-based simulation. The connected simulation and optimization modules can enhance the production logistics significantly, potentially providing a reference approach for similar industry applications.

Simulation is a well-established planning aide for planning purposes in production environments Michaloski et al. Despite the availability and acknowledged potential, the practical application is still scarce, as both a literature review Jahangirian et al. A major hurdle is the perceived difficulty of designing models and acquiring proper data as well as the scarcity of reference applications with significant shown benefits.

This paper is aimed at contributing to the understanding of potential benefits of simulation applications for practical planning purposes, especially for small and medium sized companies SME , that find it particularly hard to cope with complex planning situations and the application of advanced planning techniques. The paper is based on a complex planning case for a food manufacturer in Europe, in which a multi-module simulation based planning method was developed and applied.

The cased study results are discussed. The paper is structured as follows: After an introduction of the case study and a general introduction of the planning approach, the three major modules of the approach are presented.

The paper will finish with a summary discussion of the results and an outlook on future research. The case study is based on a food manufacturer in Europe that produces goods for supermarket chains and wholesale, also located in Europe. The goals for the planning mainly consist of calculating the necessary amount and capacity of production and logistics resources, while at the same time improving the productivity of the system, which in turn minimizes the investment and operational cost for the new plant.

Figure 1 offers a simplified overview of the main production process. Figure 1: Simplified process overview of the production facility of the case study. In this work, the researchers undertake a root-cause enabling Vendor Managed Inventory performance measurement approach to assign responsibilities for poor performance. Additionally, the work proposes a solution methodology based on reinforcement learning for determining optimal replenishment policy in a VMI setting.

Using a simulation model as a training environment, different demand scenarios are generated based on real data from Infineon Technologies AG and compared based on key performance The purpose of the article is to create a predictive analytics simulation model to help managers anticipate manufacturing issues.

It integrates specifically the involvement of human resources in the manufacturing systems. The predictive analytics simulation model also includes the main existing interactions between the operators and the manufacturing system.

This paper proposes a simulation-based decentralized planning and scheduling approach to improve the performances of a job-shop production system, compliant with a semi-heterarchical Industry 4. To this extent, to face the increasing complexity of such a scenario, a parametric simulation model able to represent a wide number of job-shop systems is introduced. Pallets are returnable transport items and of great importance for supply chains.

They ensure efficient storage, transport, and handling processes. The pallet cycle, however, is associated with a substantial effort. In addition to administrative costs, extra trips and detours must often be taken by forwarders to retrieve pallets or buy new pallets. In this paper, a fictitious cross-actor pallet exchange platform is analyzed by building a supply chain model. To solve the problem, intelligent, adaptable, and autonomous systems have been developed using machine learning and simulation to sequence operations under uncertainty within large manufacturing systems.

This work aims at optimizing a public transportation network and its maintenance. In particular, it focuses on determining routes for replacement services and adjusting headways in case of scheduled shutdowns of subway lines.

A simulation-based two-layer optimization approach is proposed to solve the problem. Factors including hospital space layout, patient behavior, patient flow, and medical procedures interact and relate to each other, and ultimately affect efficiency and performance of healthcare facilities.

This research integrates discrete event simulation DES and agent-based simulation ABS to help managers examine, plan, and compare different spatial design schemes through the modeling of patient behavior, patient This paper focuses on optimizing the production of a real-world pre-assembly facility in a high-volume and high-mix semiconductor wafer fab.

In simulation software, the researchers built an in-depth, deterministic discrete-event model. With it, they tested release policies in two stages, using real production data and demands. Back to papers. Deep Reinforcement Learning Approach for Inventory Policy Tested in Simulation Environment In this work, the researchers undertake a root-cause enabling Vendor Managed Inventory performance measurement approach to assign responsibilities for poor performance.

Building a Predictive Analytics Simulation Model of a Semiconductor Manufacturing Facility The purpose of the article is to create a predictive analytics simulation model to help managers anticipate manufacturing issues. Simulation-Based Scheduling and Planning Approach to Job-Shop Production System This paper proposes a simulation-based decentralized planning and scheduling approach to improve the performances of a job-shop production system, compliant with a semi-heterarchical Industry 4.

Simulation-Based Transportation Network and Maintenance Optimization This work aims at optimizing a public transportation network and its maintenance.

Planning and Management of Hospitals and Other Healthcare Facilities: Layout Comparison Factors including hospital space layout, patient behavior, patient flow, and medical procedures interact and relate to each other, and ultimately affect efficiency and performance of healthcare facilities. Optimizing Semiconductor Production Process with Simulation Software This paper focuses on optimizing the production of a real-world pre-assembly facility in a high-volume and high-mix semiconductor wafer fab.

Simulation-Based Case Studies in Logistics: Education and Applied Research by Yuri Merkuryev

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Simulation-based Case Studies in Logistics” presents an intensive learning course on the application of simulation as a decision support tool to tackle complex DRM-free; Included format: PDF; ebooks can be used on all reading devices based on the results of applied research, covering application areas such as.


Simulation-Based Case Studies in Logistics

Once production of your article has started, you can track the status of your article via Track Your Accepted Article. Help expand a public dataset of research that support the SDGs. Transportation Research Part E : Logistics and Transportation Review publishes informative and high quality articles drawn from across the spectrum of logistics and transportation research.

Simulation-based Case Studies in Logistics presents an intensive learning course on the application of simulation as a decision support tool to tackle complex logistic problems. The book describes and illustrates different approaches to developing simulation models at the right abstraction level to be used efficiently by engineers when dealing with strategic, tactical or operational decisions in logistic systems. Simulation-based Case Studies in Logistics is an essential text for postgraduate engineering students and researchers working in the area of logistics modeling and simulation. The study of security has been dominated for four decades by a scientific perspective that has been under attack since the end of the Cold War.

To cope with these uncertainties and the multiple objectives in the model, we applied an interactive fuzzy framework. Furthermore, the viability and effectiveness of the model and the framework are explored with a number of sensitivity and business analyses.

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