The core of our technology is the CI PEAST Algorithm. The algorithm evolved from two doctoral dissertations by our founder members. The acronym PEAST stems from the CI methods used as Population, Ejection, Annealing, Shuffling and Tabu. The algorithm is based on the computational collaborative intelligence. It has a unique intelligent skill to explore and find the best promising solutions.
There is a big difference between real artificial intelligence and artificial artificial intelligence. Real AI works intelligently without human control and learns to work better in time without human control. Our PEAST Algorithm has real computational intelligence. We have a genuine CI story to back this up. The algorithm automatically finds the best possible parameter values to guide the optimization process. The parameter values are verified in the implementation phase. The algorithm is capable of adjusting and calibrating itself based on its own experience, thus learning to operate even better in time.
Our algorithm’s effectiveness and efficiency have been shown in the open-access scientific performance tests, examples of which are staff rostering, shift generation, days-off scheduling, sports league scheduling, partial round robin tournaments, balanced incomplete block design, school timetabling, course selection, generalized assignment problem and modified transportation problem.
Our computational intelligence technology, the CI PEAST Algorithm is based on more than 20 years of research work on mathematics, algorithms and optimization. The effectiveness and efficiency of the CI PEAST Algorithm has been shown in the open-access scientific performance tests. During the last ten years, we have published more than 60 international research articles on the use of CI.
Our optimization works in the real world. The real-world cases solidly proves the value of our work. For example, it is highly important for our social and health care sector customers to generate shifts that follow the patient flow, for our transportation company customers we need to generate rosters to the exact required number of minutes and for our major sports league customers it is vital to generate fixtures that secure their profit.
Our ground-floor understanding of how to run projects verifies that the customer will achieve the agreed results. We believe in genuine, objective and sharp prestudy of customer’s need and the problem in hand. This will pay itself back ten times if not more in the implementation phase. We also firmly believe in continuous dialog and co-learning in the production phase.
“We modernized our workforce management process. Hundreds of employees are now rostered simultaneously.” (Management Director)
“I do not want to roster any more without optimization” (Personnel Planner)
“We centralized our scheduling and several work units are now optimized together. We can now simultaneously optimize productivity and employee satisfaction. Both have clearly increased” (CEO)
“We wanted to secure the interest of media as well as our revenues. The total number of spectators has increased once we started to use optimization” (CEO)
We offer our potential customers a chance to test the value of our optimization for free or for very low cost depending on the required prestudy time. For example, we can either reproduce one of the realized schedules, resource usages and/or structural choices or produce a test case for the future. The customer can then study the test result to assess the value of our optimization.
A genuine dialog between us and the customer is vital in generating optimization results of superior quality. We believe in deep enough prestudy of potential customer’s need. The prestudy will show the tangible profits the customer can gain implementing our technology. Or the prestudy can as well show that no sufficient financial, operational or welfare benefits can be realized.
There is actually a very short route from Proof of Value to fast prototyping.
CI Parallel Computing Platform