Brest State Technical University, Intelligent Information Technology Department
From Students' Works (2012)
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- A visualisation of evolution using 2-D function
- How the initial random population converge to the solution on a 2-D graph? ... Koshkevich Anna (2008)
- Initial generation
Now

- Intermidiate generation-1

- Intermidiate generation-2

- Almost final generation

- What if we have many local minimum? ... By Vinnikov Artem (2010)
- Initial generation

- All chromosomes converged to the solution.

- Another example of a function with many local minimum? ... By Hrechka Alesia (2010)
- Initial population

- Again all chromosomes converged to the global solution.

- What if graph has GLOBAL not local multiple peaks?
- Visualize how population converge to soloutions on a 2-D graph with 5 peaks ... Koshkevich Anna (2008)
- Initial generation

- Intermidiate generation-1

- Intermidiate generation-2

- Final generation

- Multimodal Optimization
- Visualize how population converge to soloutions on a 2-D graph with 5 peaks ... Mezian Andrey (2010)
- Initial generation

- Intermidiate generation-1

- Intermidiate generation-2

- Knap-sack Problem
- With a knap-sack whose capacity is 100kg, we maximize total price of the items we can carry in the knap-sack ... Nikonovich Valentin (2010)
- Pre-specified 100 items and weight and price of each item:
(item, weight, price) = (#1, 0.49kg, $59.52)(#2, 0.75kg, $11.98)(#3, 0.77kg, $49.77)(#4, 0.45kg, $9.48)(#5, 0.87kg, $80.70)(#6, 0.60kg, $81.09)(#7, 0.60kg, $12.00)(#8, 0.22kg, $82.58)(#9, 0.59kg, $85.10)(#10, 0.76kg, $19.77)(#11, 0.71kg, $69.20)(#12, 0.96kg, $31.37)(#13, 0.52kg, $16.05)(#14, 0.45kg, $47.31)(#15, 0.73kg, $64.51)(#16, 0.51kg, $26.63)(#17, 0.07kg, $51.53)(#18, 0.03kg, $40.75)(#19, 0.88kg, $8.22)(#20, 0.78kg, $12.29)(#21, 0.57kg, $72.72)(#22, 0.81kg, $83.26)(#23, 0.00kg, $35.93)(#24, 0.04kg, $15.50)(#25, 0.78kg, $95.82)(#26, 0.55kg, $88.15)(#27, 0.49kg, $31.78)(#28, 0.64kg, $5.79)(#29, 0.09kg, $54.76)(#30, 0.49kg, $66.61)(#31, 0.35kg, $20.71)(#32, 0.62kg, $52.34)(#33, 0.50kg, $1.72)(#34, 0.14kg, $63.80)(#35, 0.21kg, $64.92)(#36, 0.39kg, $75.59)(#37, 0.80kg, $29.14)(#38, 0.47kg, $71.06)(#39, 0.94kg, $37.52)(#40, 0.48kg, $17.43)(#41, 0.65kg, $53.51)(#42, 0.54kg, $15.92)(#43, 0.21kg, $34.04)(#44, 0.59kg, $49.37)(#45, 0.72kg, $41.22)(#46, 0.16kg, $17.66)(#47, 0.05kg, $43.81)(#48, 0.38kg, $17.02)(#49, 0.88kg, $30.64)(#50, 0.70kg, $6.57)(#51, 0.97kg, $8.04)(#52, 0.29kg, $13.57)(#53, 0.73kg, $10.80)(#54, 0.79kg, $37.03)(#55, 0.95kg, $28.93)(#56, 0.26kg, $0.03)(#56, 0.51kg, $83.32)(#58, 0.37kg, $55.60)(#59, 0.98kg, $64.54)(#60, 0.14kg, $2.85)(#61, 0.82kg, $14.20)(#62, 0.07kg, $41.50)(#63, 0.47kg, $93.02)(#64, 0.06kg, $60.88)(#65, 0.21kg, $67.95)(#66, 0.35kg, $27.25)(#67, 0.81kg, $18.98)(#68, 0.89kg, $68.68)(#69, 0.84kg, $14.15)(#70, 0.17kg, $51.24)(#71, 0.43kg, $20.15)(#72, 0.43kg, $69.67)(#73, 0.99kg, $41.93)(#74, 0.55kg, $96.97)(#75, 0.25kg, $87.40)(#76, 0.18kg, $62.32)(#77, 0.15kg, $87.67)(#78, 0.28kg, $24.09)(#79, 0.54kg, $27.50)(#80, 0.79kg, $31.50)(#81, 0.92kg, $95.18)(#82, 0.32kg, $91.21)(#83, 0.53kg, $85.76)(#84, 0.47kg, $8.24)(#85, 0.43kg, $84.92)(#86, 0.60kg, $5.55)(#87, 0.38kg, $49.72)(#88, 0.30kg, $19.97)(#89, 0.68kg, $75.96)(#90, 0.55kg, $36.08)(#91, 0.86kg, $30.28)(#92, 0.04kg, $11.12)(#93, 0.10kg, $55.24)(#94, 0.44kg, $61.36)(#95, 0.08kg, $17.03)(#96, 0.47kg, $95.87)(#97, 0.48kg, $68.91)(#98, 0.85kg, $82.75)(#19 0.07kg, $17.35)(#100, 0.17kg, $49.87)
- Fitness vs. Generation
- Traveling Salesperson Problem (TSP)
- First, 11 cities are created at random. Then a genetic algorithm was applied. ... Yarmak Natalia (2010)
- Cordinates of 11 cities

- Distances between two cities

- Fitness vs. Generation

- Obtained (possibly) the shortest tour

- Sorting Network ... Yarmak Natalia (2010)
- Fitness vs. Generation

"How does the final chromosome above look like?"
- Can we find a lucky dog among those who explore a grid-world looking for a sausage starting from home?
- Try to cut two parent-chromosomes at different points instead of a same point such as a standard GA ... Valery Mikhnevich (2010)
- Initial generation: Among routes of many unlucky dogs (black) we can see the route of a lucky dog (yellow).

- Final generation without mutation

- Final generation without mutation

- Yet another result for the same task as above ... Valentin Nikonovich (2010)
- A route of a dog in the initial population, the final route of the successful dog, and evolution curve.

- So far so good! But can the lucky dog go back to home again? --- An implementation by the standard GA ... Lavriniuk Roman (2010)
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