DIPLOMA THESIS EVALUATION

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DIPLOMA THESIS EVALUATION

Student´s name and surname: Gnanasekar Pandiyaraj

Name of the diploma thesis: Development of Evolution Algorithm for Shop Scheduling Problem Supervisor of the thesis: Ing. František Koblasa, Ph.D.

1. Diploma thesis evaluation

Evaluation excellent excellent

minus very good very good

minus good failed

Meeting the goal and fulfilling

task of the thesis X

Quality of conducted survey X

Methodology of solutions X

Expert level of the thesis X

Merit of the thesis and its

potential applicability of results X Formal and graphic level of the

thesis X

Student´s personal approach X Mark x in the corresponding box.

Supervisor´s final evaluation is based on his/her overall subjective evaluation.

Grading is stated literally in the article no. 5, neither by a number, nor by a letter.

2. Comments and remarks on diploma thesis:

The main goal of the thesis was to develop a new algorithm to optimize production scheduling in the specific environment of Job shops. The student follows the regular steps of scientific work. After literature review, know strategies beginning with commonly used dispatching rules and simple genetic algorithm were tested to put base stone for experimental comparison of the new algorithm. Student developed own elimination strategy with motivation to reduce population convergence. The student compares several strategies base on the ability to find optimal or near-optimal solutions together with optimization timespan. Ability to improve solutions during on the fly optimization (comparison of improvement and optimization time) was also considered.

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3. Questions about diploma thesis:

• Pg. 22 – why do you count simulated annealing and tabu search as evolution techniques?

• Pg. 34 – please explain order crossover.

• Pg. 49 – How do you check uniqueness (base on what)?

• Pg. 46-47 and 53-54 How was a gap (distance fro optimum) at Table 2 - 5 calculated?

• Pg. 49 resp. 52. Your rejected pool is equal to the size of the population while the mating pool is half of the population. Do you sort rejected pool and check for uniqueness every generation (e.i. you apply an elitist strategy for the rejected pool)?

• How replacement strategy works after the first generation when there is 1,5 population size of individuals available?

4. Supervisor´s statement on results of the inspection carried out by the anti-plagiarism program in the STAG system:

According to the control in information system STAG, this thesis work is original – without plagiarism.

5. Supervisor ´s grading of the diploma thesis:

Excellent minus

Date: 18.6 2020 , in Liberec

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Supervisor´s signature