1 paskaita Flashcards
anyLogistix
supply chain analytics software to design, optimize and analyze your company’s supply chain.
anyLogistix problem examples:
- Where are the best locations for our warehouses, distribution centers and production sites?
- What are the best policies for sourcing and transportation?
- How resilient is our supply chain?
Model-based Decision-Making in Supply Chain Management:
- Management problem
- Mathematical model
- Algorithm
- Software and Solution
- Managerial solution
Management problem:
we can observe that a real management problem is the initial point of the decision-making process. For example, this could be a facility location problem where we are trying to decide where to locate the facilities and which quantities should be shipped from the facilities to the markets.
Mathematical model:
the next step is to transform the real problem into a mathematical model. For this transformation, we need to reduce the complexity of reality or in other words simplify the reality. For example, we aggregate demand into fixed quantities instead of considering fluctuations in demand.
Algorithm:
the simplifications are necessary to represent the management problem as a mathematical model. This model can then be solved with the help of existing algorithms in a reasonable time. In our example, we formulate the facility location problem as a mixed-integer linear programming model that can be solved with the help of simplex and branch&bound algorithms.
Software and Solution:
for implementation of the mathematical model, software is needed. For example, the professional solver CPLEX is used in anyLogistix. Software will calculate the solution. In our example, the solution would include suggestions on where to open facility locations and which product quantities should be shipped from each opened facility to each of the markets so that total production and logistics costs are minimal.
Managerial solution:
however, it is important to consider whether this solution is automatically our decision. NO! This is a solution to the mathematical problem. Management expertise is needed to transfer this mathematical solution into managerial decisions. First, the simplifications of reality should be reviewed. Second, so called soft facts such as risks, flexibility, etc. should be included in the analysis. This need for managerial expertise is why we call these models decision-supporting quantitative methods.
Green Field Analysis (GFA)
- The objective of the green field analysis (GFA) is to determine the best location for our distribution center. We want to find the location that allows us to fulfil our customer demands at the lowest total transportation cost.
- The best location is determined by finding the point at which the sum of the distance from the warehouse(s) to the customers, weighted by their respective demands, is minimal
GFA problem examples
Where are the best locations for our warehouses, distribution centers and production sites?
The issues we need to consider during a green field analysis:
our customers’ locations, the distances from our warehouse(s) to our customers, and our customers’ demands for our products.
Network Optimization (NO)
- The objective of the network optimization (NO) is to find the optimal combination of factories and/or distribution centers in the supply chain
- The solution should match supply and demand, as well as find a network configuration with the lowest costs
- NO allows to compare alternative network designs according to a cost objective function
- Not time dependent
Data required for NO:
- Alternative facility locations
- Customers (demand & locations)
- Factory costs (fixed and production costs)
- DCs costs (fixed, carrying/holding, in- & out-bound processing costs)
- Transportation costs
- Truck load capacity and speed
- Product purchasing costs
- Min & max capacities of facilities
NO outputs are:
- Facilities to be included
- Flows from/to different facilities
NO problem examples:
- Where are the best locations for our warehouses, distribution centers and production sites?
- How to allocate demand and supply in a complex network?
