What is supply chain's & logistics networks modelling?

When a company designs its new logistics network, it will consider all aspects of the site, such as the customer market, employee associations, quality of life requirements and government incentives. After analyzing these elements, you can create models that will allow companies to better understand their decisions.

There are a number of modelling methods that can be used, each with its own advantages and disadvantages. This article will focus on the different types of modelling methods that can be used to support decisions made.

Modelling methods

Using modelling methods is important for companies that choose a new logistics network. Different modelling methods allow companies to look at their comparison, cost-effectiveness and customer service efficiency in a range of advanced logistics networks. Companies can look at different modelling techniques and decide which is best for networking opportunities.

Optimized Modelling

The optimization model is derived from precise mathematical procedures that offer the best or optimal solution based on the mathematical formula used. This model is based on a mathematical formula only.

This means that there is no subjective access to the model, only assumptions and data. The optimization model covers data such as the level of customer service available, the number and location of distribution centers, the number of production sites, the number of distribution centers allocated to the production plant, and the inventory. 

Which needs to be maintained?

One of the optimization models used for logistics networks is the linear programming model, sometimes called LP. This is particularly useful for linking supply and demand constraints to manufacturing enterprises, distribution centers and markets.

In relation to the aim of reducing costs, linear programs can determine the optimum distribution model of devices based on the constraints identified. However, when using mathematical formulas, there is no contribution to the subjective contribution.

Simulation models

A simulation model is defined as creating a real-world model. Once the model has been created, you can carry out experiments on the model to see how changes made to the model can affect the total cost of the logistics network.

For example, by changing network restrictions, a simulation model can help determine how this affects the economic efficiency of a whole network.

To make the simulation model effective, a significant amount of data on traffic, storage, labour costs, materials processing and inventory needs to be collected so that changes are made to these changes correctly when changes are made to the restriction model. . 

However, changes in the simulation model do not create an optimal logistics network created by the optimization model; only the changes made to the model are being assessed. This type of model is very useful when companies make general network decisions and want to see the overall impact of all the changes.

Heuristic model

As simulation models, heuristic models do not create a best solution for logisticsnetwork.

The heuristic model is used to reduce a major problem to a more acceptable size. It should be noted that heuristic models do not guarantee solutions and that many heuristic models can conflict or give different answers to the same question and still useful for creating a logistics network in general.

Heuristic models are often referred to as a “rule”, which can be useful in creating a logistics network.

For example, a heuristic model can be used to determine the best location of a distribution center at least ten miles from the market, fifty miles from the main airport and more than three hundred miles from the nearest distribution center. The heuristic model will cover all areas that suit specific parameters and find areas that are most appropriate.