Category archives: App development
Do you know Set is a god of the desert, storms, disorder, violence and foreigners in ancient Egyptian? So it is totally possible that his disturbance power influenced mathematical world, which is considered employing set theory as foundation system. From 5th century Greek in west India in the east to today’s modern society, there are struggles, debates, paradoxes around set theories. You can find lots of readings about them, or if reading history sounds boring, there will be a little fun video to watch at the end of this blog.
Set in AIMMS can also be confusing for new AIMMS users. We often get questions regarding how to use set, subset, indices, mappings, etc. While working on my own Fantasy Football project, I think it might be helpful to share how I started building one of my models to clarify some of the ambiguity by this example.
In preparation for the INFORMS Business Analytics conference in Florida, we wanted to experiment with a new approach for our regular pre-conference workshop. We wanted to engage the audience much more during the session, and do so in a fun and interactive way.
A couple of weeks prior the conference, we sat down and discussed how we could achieve this goal. Almost immediately, we considered the idea of doing a reduced version of our proof of concept (POC). The recently improved POC has proven to be a method that successfully demonstrates the value of AIMMS. It demonstrates just how quickly an AIMMS-based decision support application can be developed and deployed. Our regular POC is a two-day process that starts by defining the problem on a whiteboard with a prospect. The information shared on the whiteboard is then translated into the AIMMS modeling language. Shortly thereafter, an end user application is created on top of the model.
The famous travelling salesman problem (TSP) deals with the following problem: given a list of cities and the distances between each pair of cities, a salesman has to find the shortest possible route to visit each city exactly once while returning to the origin city. One way to formulate the TSP is as follows:
min sum( (i,j), c(i,j)*x(i,j) ) (1) s.t. sum( i, x(i,j) + x(j,i) ) = 1 for all j x(i,j) binary for all i > j
Here x(i,j) equals 1 if the route from city i to city j is in the tour, and 0 otherwise. Note that this is the formulation for the symmetric TSP in which the distance from i to j equals the distance from j to i. This formulation is not complete as it allows for subtours. One way to exclude these subtours is by using subtour elimination constraints (SECs for short):
sum( (i,j) | i in S and not j in S, x(i,j) + x(j,i) ) >= 2 for all S, 1 < |S| < n
Here S is a subset of cities while n denotes the number of cities. This SEC enforces that at least one route is going from a city in set S to a city outside S.
The goal of this article is to explain how you can control errors and warnings within AIMMS. Namely, we will walk you through some useful tips that can help you manage errors and warnings in the best possible way to create better models.
Modeling the forest: Ontario’s Ministry of Natural Resources takes us through decades of effective forest managementPosted on April 01, 2014 by Deanne ZhangLeave a reply
Forest ecosystems are highly complex and influenced by a diversity of factors. Sustainable forest management is therefore an ongoing and constantly evolving process which requires an integrated approach. Government bodies, such as The Ontario Ministry of Natural Resources (OMNR), must conform to provincial policies and standards, while taking economical and ecological considerations into account to arrive at optimal forest management policies. OMNR manages 27 million ha of Ontario’s public forest and has been using an AIMMS-based model for this purpose since 1994. The Strategic Forest Management Model, or SFMM, enables foresters to analyze the relationships between forest condition, silvicultural practices, wood supply and potential wildlife habitat. This analysis enables them to understand how a forest develops through time and explore alternative forest management strategies and trade-offs. Today, nearly 2 decades after its launch, we spoke with Dirk Kloss, OMNR’s Resource Modeling Specialist, to find out where SFMM stands today and what their experience using AIMMS has been like.
Using operations research to solve pressing global issues: the mathematical story behind North Star Alliance’s POLARISPosted on November 26, 2013 by Chris KuipLeave a reply
More than 35 million people worldwide are infected with HIV or are living with AIDS, and approximately 70% live in Sub-Saharan Africa. Mobile populations, such as long distance truck drivers, are particularly at risk of contracting and transmitting the virus. In 2007, TNT Express and the United Nations World Food Programme joined forces to form North Star Alliance (North Star) – a public-private partnership that is working to increase access to health services along major transport corridors in sub-Saharan Africa. ORTEC, a longstanding AIMMS partner, joined North Star in 2008 to design their award-winning Corridor Medical Transfer System (COMETS), which enables North Star staff to access and monitor patient health data across boarders and throughout its network of clinics. ORTEC has also contributed to North Star by developing POLARIS, an innovative application built on the AIMMS optimization platform that helps the organization improve their planning and decision-making on the ground. In this blog post, we will explore the POLARIS Supply Chain Model developed by Harwin de Vries while at ORTEC.
AIMMS models can be very complicated, with lots and lots of identifiers, procedures, pages and menus. You probably know that AIMMS has a search functionality in the model explorer, allowing you to find references to a particular identifier in the complete model. But did you also know that AIMMS offers you the possibility to find out in which page an identifier is being used? You can even find the object in which the identifier is located using AIMMS.
Professors, students, and practitioners of operations research can choose from a variety of tools when conducting research and delivering results. When it comes to solving math programs and optimization problems, there are many options, such as using a math modeling tool, a generic programming language with an API, or a solver directly.
As someone who is new to AIMMS and has done all of the above for doing research and providing solutions, there are several reasons why I prefer to use AIMMS. Here are the top 5 reasons:
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