Please refer to the file attached and strictly follow the instructions and rubric mentioned in the...

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Please refer to the file attached and strictly follow the instructions and rubric mentioned in the file.

Assessment 2 (Individual Assignment) Assessment 2 (Individual Assignment) There are a number of typical models in the Operations Research field which can be applied to a wide range of supply chain problems. In other words, by learning a typical model various problems in supply chain optimisation domain can be addressed. Please note that the basis of all proposed problems is the methods that you have learned in this course; however, none of them has been directly taught. The reason behind the design of this assignment is that there are hundreds of problem variations with the same structure in the real business world. Therefore, by learning the linear programming, students should be able to formulate a solution for problems which have a similar structure to a typical problem. Students are required to research one of the proposed topics and address the assignment requirements accordingly. Step 1: Identify and Solve a Typical Problem Select one of the following typical models: • Travelling Salesperson Problem (TSP) • Multiple Traveling Salesman Problem (mTSP) • Vehicle Routing Problems (VRP) • Job Shop Scheduling • Parallel Machine Scheduling • Pickup and Delivery • Flow Shop Scheduling • Travelling Thief Problem • Christmas Lunch Problem • Newsvendor Problem • Knapsack Problem • Eight queens Problem • Minimum Spanning Tree • Hamiltonian Path problem 1.1. Background: • Provide a detailed explanation of the selected problem. 1.2. Model • Provide typical mathematical model of the selected problem and clearly explain different aspects of the model (e.g. decision variable, objective function, constraints, etc.) 1.3. Solving an Example • Develop a mathematical model for a workable and reasonable size of the problem. – For many typical problems, when size of the problem increases, it becomes NP-Hard. In other words, your computer will not be able to solve it mathematically. Therefore, ‘workable and reasonable size’ here means that size of the selected problem should not be too small or too large. • Solve the problem in Excel and transfer your solution to Word. It is required that the details and steps of getting the solution are provided in the Word document. • Interpret the findings and discuss. Step 2: LR on Application of Selected Typical Model in Design and Analysis of Supply Chain • Identify at least 5 peer reviewed articles in which your selected typical problem has been employed to address knowledge gaps in the supply chain field. 1 – At least one of the selected articles should be published after 2010. • Write a comprehensive literature review on the application of “your selected” typical model in design and analysis of supply chain and address the following (but not limited to) points: – What type of problems in a supply chain can be addressed by the selected typical problem? – Compare similarities and differences of selected articles. – Discuss the suitability of using the selected typical model in design/analysis of various supply chains. – What are the limitations of your selected typical problem? – Undertaking any additional critical and/or content analysis on the application of selected typical problem in design and analysis of supply chain is highly recommended. Step 3: Summary of Findings • A summary of findings regarding the strengths and weaknesses of the selected typical problem in design and analysis of supply chains should be summarised in this section. Note: • From each article, something unique should be explained in the report. • Word limit: 2500 ± 500 words • As an RMIT Business student, you are required to use the Harvard referencing system. • The naming convention for both Word and Excel files is: ‘Student Number_Student Name’. Both Word and Excel files should be uploaded to the Canvas. Rubric: The assignment report is marked based on the following rubric: Criteria Description Weight Background of Typical Problem Refer to the assignment description 10% Model Refer to the assignment description 20% Solving an Example Refer to the assignment description 15% Literature Review Refer to the assignment description 40% Summary of Findings Refer to the assignment description 5% Presentation Quality of writing, grammar, citations, references, format and structure of report, captions, etc. 10% 2 Step 1: Identify and Solve a Typical Problem Step 2: LR on Application of Selected Typical Model in Design and Analysis of Supply Chain Step 3: Summary of Findings Note: Rubric:

assignment2-wddwgsaj.pdf

Jose · Accepted Answer

Vehicle Routing Problem 
Student Name
Instructor Code
1.1 Background
The literature and social production practises have established transportation planning as a prominent issue. Vehicle routing problems (VRPs) and its variations are being studied by a growing number of academics in real-world applications and scenarios. Furthermore, with the continuous advancement of computer processing speed and memory capacity, a variety of methods may be utilised to answer increasingly complicated VRPs (Demir et al 2021). The Vehicle Routing Topic (VRP) is a well-known operational research problem in which clients with known requests are serviced by one or more depots. The goal is to discover a set of delivery routes that meet specific requirements or limits while costing the least amount of money overall. Most of the companies are facing different logistics issues, it is not easy for the companies to develop effective plans for managing the issues related to logistics activities. Vehicle routing always create challenges for the companies and the companies has to develop productive strategies and methods to making it effective.
2.2 Model
According to the VRP definition, m trucks will initially be stationed in a depot and will transport discrete quantities of commodities to n clients. A VRP challenge is determining the best route for a group of vehicles to take when serving a group of people. The goal is to keep the entire transportation costs as low as possible. 
Decision variable of the problem 
Driver working hours, work hours and traffic conditions. 
Constraints 
1. Each truck must return to the depot, where the subscript is zero, 
2. Assures that each node in a route is only accessed once. 
3. Specifies that whenever a vehicle arrives at a node, it must depart from that node in order to maintain route continuity (Vidal et al 2020). 
The answer to the basic VRP problem is a set of routes that all start and terminate in the depot and satisfy the constraint of only serving each client once. The cost of transportation can be reduced by lowering the overall distance travelled and the number of vehicles necessary. 
3.3 Solving the Problem
Total DD – 125
Vehicle Capacity -70 
First Step
Enter Data in to the excel, we have to enter three aspects;
1. Demand of each store
2. Vehicle capacity
3. Distance matrix
Step 2
Enter the decision variable 
Binary Variable and Quantity
Step 3
Adding Constraints
Step 4
Run Solver Model by Using LP
3.4 Literature Review
Vehicle routing challenges are problems that arise from the circulation of products between warehouses and clients (VRPs). Dantzig and Ramser introduced the VRP in 1959 to simulate how a fleet of homogenous vehicles might satisfy demand for oil from a variety of gas stations with a minimum travel distance from a central hub. Clarke and Wright introduced further practical limits to VRPs five years later, requiring that items be delivered to each consumer within a set of boundaries. The VRP with time windows (VRPTW) is a sort of problem model that has become one of the most frequently studied issues in the field of operations research (Wang et al 2019). Current VRP models, on the other hand, differ dramatically from those proposed by Dantzig and Ramser and Clarke and Wright in that they attempt to account for real-world complexity. VRPs are one of the most important difficulties that logistics organisations face, and as a result, a growing amount of research is concentrating on them (Snyder et al 2018). 
Because real-world issues entail complicated restrictions such as time windows, time-dependent journey times (representing traffic congestion), various depots, and diverse fleets, solving VRPs is computationally costly and classified as NP-hard. These characteristics add a lot of complexity to the VRP research environment and have changed it considerably (Li et al 2019). Computer processing speed and memory capacity have quickly increased, allowing for the processing of more complicated VRPs and the widespread use of logistical distribution scenarios. Over the last few decades, the number of VRP solution techniques published in academic journals has exploded. The VRP represents a rapidly changing subject of operations research that has been increasing at a pace of 6% per year, making it challenging to keep up with advances and have a clear picture of which variations and solution techniques are relatively new (Jabali et al 2019). The VRP family may be thought of in two ways: (1) the number of potential solutions, which grows exponentially with computer science and algorithm design; and (2) the number of conceivable issue variations, which grows exponentially with a variety of problem features as well.
According to the words of Pasha vehicle routing problem helps for identifying the best routes for completing the logistics activities (Pasha et al 2020). The primary goals are to discover the smallest number of cars, the shortest trip time, and the cheapest routes possible. In reality,

Assessment 2 (Individual Assignment) Assessment 2 (Individual Assignment) There are a number of typical models in the Operations Research field which can be applied to a wide range of supply chain...

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