代写BUSML4385 in Supply Chain Optimization and Simulation using anyLogistix代写Web开发
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in Supply Chain Optimization and Simulation using anyLogistix
Level 1 Basic
2. Introduction
Supply chain network design and operational planning decisions can have a drastic impact on the profitability and success of a company. Whether to have one warehouse or two, close a factory or rent a new one, or to choose one network path over another are all consequential decisions a supply chain (SC) manager must make. However, these decisions must be the result of more than experience or intuition, and, as a result, research in SC management (SCM) is geared towards providing the data, tools, and models necessary for supporting SC managers’ decisions. One of these decision-supporting tools is anyLogistix (ALX), a software which facilitates Greenfield Analysis (GFA), Network Optimization (NO), and Simulation (SIM).
ALX has become more and more popular with the provision of the free PLE version, and because it is an easy-to-use software, includes simulation and optimization, and covers all standard supply chain topics (center-of-gravity, efficient vs responsive SC design, SC design through network optimization, inventory control simulation with safety stock computations, sourcing (single vs. multiple) and shipment (LTL vs FTL) policy simulation). This case booklet has been developed to support a course in Supply Chain Management using ALX software and its sample case (Polarbear Bicycle) analysis. The following themes will be considered:
• Facility Location Planning (COG, Trade-off Efficiency vs Responsiveness)
• Supply Chain Design (Network optimization, CPLM)
• Inventory Control Policy (simulation, safety stocks, ordering policies)
• Sourcing Policy (simulation, single vs multiple sourcing)
• Shipment Policy (LTL/FTL, aggregation rules)
This collection of exercises is designed as an application add-on to the main ALX Handbook which provides technical descriptions of how to build ALX models. The main ALX handbook is available at https://www.anylogistix.com/resources/books/alx-textbook.
The ALX case booklet and handbook addresses the application of quantitative analysis methods and software to decision-making in global supply chains and operations. Understanding optimization and simulation methods in supply chain strategies is a core component to build strong decision-making skills. Completion of the exercises in this booklet will provide basic technical skills in the use of simulation and optimization software with the help of ALX software.
This case is designed to stimulate and enhance conceptual and analytical decision-making skills in actual operating situations. Students will be required to evaluate actual business situations and apply their relevant skills, experience, and judgment to develop viable resolutions to business problems using a professional supply chain simulation software tool for decision-making support. The case isdrawn from anactualindustry examplewheremanagers faceddecisions in different facets of supply chain and operations management (SCOM). The case method requires you to prepare a decision based on careful evaluation of case facts and numbers to the extent possible. As with all business situations, there may be insufficient facts, ambiguous goals, and dynamic environments.
Upon completing the case, students should be able to do the following:
• Develop critical thinking skills, be able to identify, generalize, prioritize, isolate, and reduce complexity in complex and ambiguous operational situations,
• Understand how strategic considerations influence operational decisions,
• Apply analysis and improvement tools learned in previous courses to actual business situations,
• Strengthen qualitative and quantitative reasoning skills for operational decision-making. Specifically, this case seeks to strengthen the following skills:
Analytical Skills: Students will possess the analytical and critical thinking skills to evaluate issues faced in business and professional careers.
Technical Skills: Students will possess the necessary technological skills to analyze problems, develop solutions, and convey information using optimization and simulation software.
To develop these skills, the case will examine the Polarbear Bicycle case. Students will act as managers in the firm to determine the best course of action for building a new supply chain
(SC) from scratch. The goal of the case and ALX analysis is to develop a new SC for the
Polarbear Bicycle company. The new SC will need to be focused on optimization and
profitability to enhance the firm’s competitive edge in an increasingly global market where sales prices are driven down while costs remain stable.
Using the ALX data and software, students will conduct analyses to (1) determine an optimal location using Greenfield Analysis (GFA) for a new warehouse, given the location of their current customers and those customers relative demands, (2) compare alternative network designs using Network Optimization (NO), (3) perform. a Simulation (SIM) of different scenarios,
(4) validate the models using Validation, Comparison experiments, and (5) analyze SC behavior. under un- certainty using the Risk Analysis experiment.
The author thanks The AnyLogic Company for their invaluable feedback, comments and sce- nario updates to this exercise book. The author also wishes to thank Ms. Meghan Stewart for a thorough proof-reading. The author thanks students Meghan Stewart, Jannes Zuch, Chantal Reimann, Moritz Albrecht, Stephanie Paeschke, Julia Dyck, Lily Creed, Christin Kemper, Ragna Maria Berg in MA Program Global Supply Chain and Operations Management | GSCOM at Berlin School of Economics and Law for case-study samples used in this exercise book. Finally, the author thanks Mr. Nurlan Mammadzada, a former student in the GSCOM master program as well as Mr. Hiran Prathapage, a research associate at HWR Berlin for the updates of all exercises and educational materials.
3. Case study 1
3.1 Description of Case Study
We are considering a company called Polarbear Bicycle. Polarbear Bicycle has been newly founded as an e-commerce start-up selling bicycles. Polarbear’s portfolio includes four different types of bicycles: x-cross, urban, all terrain, and tour bicycles. Polarbear needs to find a good location for a new distribution center (DC). First, they estimate customer demand. Polarbear distributes their bicycles to four locations throughout Germany: Cologne, Bremen, Frankfurt am Main, and Stuttgart. Table 1 shows customer demand, which is equal to 245 bicycles per day.
|
Customer |
Bicycle Type |
Demand per day |
|
Cologne |
x-cross |
2 |
|
Cologne |
urban |
50 |
|
Cologne |
all terrain |
15 |
|
Cologne |
tour |
10 |
|
Bremen |
x-cross |
7 |
|
Bremen |
urban |
30 |
|
Bremen |
all terrain |
20 |
|
Bremen |
tour |
20 |
|
Frankfurt am Main |
x-cross |
6 |
|
Frankfurt am Main |
urban |
5 |
|
Frankfurt am Main |
all terrain |
4 |
|
Frankfurt am Main |
tour |
5 |
|
Stuttgart |
x-cross |
15 |
|
Stuttgart |
urban |
15 |
|
Stuttgart |
all terrain |
1 |
|
Stuttgart |
tour |
40 |
Table 1. Customer demand
Polarbear Bicycle has hired a consulting firm to analyze supply and distribution network alter- natives and to develop a best-case scenario for Polarbear Bicycle. They are charged with con- ducting a GFA to determine the possible location of a new DC in Germany, as well as a network optimization to compare several options for network paths. The consulting firm was also asked to run a simulation to validate several KPIs and plan inventory, and to conduct a sensitivity analysis to verify all results as well.
