Structural Optimization-Simulated annealing

Structural Optimization-Simulated annealing

1. Structural Optimization  Lecturer: Prof. Dr. Nildem TAYŞİ   Simulated Annealing (SA)  May 2023

2. Optimization Search  Techniques  Global It attempts to find the global minima or maxima of a function or a set of functions on a given set. It is usually described as a minimization problem because the maximization of the real-valued function is equivalent to the minimization of the function .  Local  It   involves finding the optimal solution for a specific region of the search space.

3. What is Simulated Annealing ?  • SA is a global optimization technique.  • SA distinguishes between different local optima. 

4. Some of Areas of Using Simulated Annealing  Engineering Design Travel Planning and Route Optimization Image and Signal Processing

5. Simulated Annealing and Civil Engineering  Some specific areas in civil engineering where simulated annealing can be used: Construction Site Layout Planning Traffic Signal Optimization Urban Planning Water Distribution System Design Geotechnical Engineering Resource Allocation and Scheduling

6. How Simulated Annealing Can Assist in Optimizing The Layout of Construction Sites. Objective Definition: The first step is to define the objective of the optimization. Initial Configuration: SA starts with an initial configuration of the construction site layout. It represents the starting point for the optimization process. Neighborhood Generation: SA explores the solution space by generating neighboring configurations from the current layout. Energy Evaluation: Each generated neighbor is evaluated using an objective function that quantifies its fitness with respect to the optimization objective.

7. 5.     Acceptance Criteria: SA employs a probabilistic acceptance criterion to determine whether to accept or reject a neighbor. Initially, neighbors with better fitness are always accepted.  6.   Cooling Schedule: The cooling schedule determines how the acceptance criteria become stricter over time, gradually converging towards a global optimum.  7.   Termination Condition: The optimization process continues until a termination condition is met. This condition can be based on reaching a maximum number of iterations, achieving a desired fitness level, or the convergence of the solution.

8. Case Study To optimize the dynamic reliability of engineering project, first of all, the author analyzed factors which affected construction quality, including the human condition, methods, machinery, and materials. Obtain the weights of various affecting factors by gray relational degree and determined the reliability improvement feasible index (RIFI). For quality, first, the system reliability optimization model is established.  Secondly, a cost function is established to analyze the changing trend of reliability in different reliability improvement feasible index (RIFI) conditions. This study used the adaptive simulated annealing algorithm and produced new creation, it computed the difference of the objective function, and then it accepted or abandoned in the process until found the optimal solution which most closed to target.

9. Reliability Analysis on Civil Engineering Project Based on SA In a civil engineering project, managers consider not only the cost and time, but also the quality and reliability. Civil engineering project reliability analysis has become an essential part of the construction process. The reliability of the civil engineering project can be affected by many factors that are dynamic change.

10. Some Factors Affecting Quality  Human factors :  Human influence is a very important factor in the project, it involves every stage of the project and affects other factors. Material factors : In the construction engineering project, materials, mainly involve all kinds of engineering materials, prefabricated parts, components, finished products and semi-finished products. Method factors : If there are incorrect or improper construction methods in the construction organization arrangement it's likely to cause  project quality problems. Mechanical factors : The control of construction machinery quality has great effect on time quality and safety of civil engineering projects. 

11. Calculating The Weights of Some Factors Affecting Quality This study adopts the gray correlation method to gain weight matrix in this section, then gets the similarity coefficient, determines the deviation degree, difference of sequence and the gray correlation coefficient, the gray correlation degree, finally the study normalizes the weight affecting quality.

12. Evaluation Matrix                    Evaluation Weight Matrix      

13. Then we calculate the  similarity coefficient by the formula:  The similarity matrix can be obtained as follows:

14. Then we calculate the deviation . We get: p = (0.0328, 0.000, 0.0080, 0.0279). Experts’ assessment deviation values that not exceed 5% are considered valid; we judge the value p < 0.05, so we consider expert evaluation results to be valid. After that we calculate the difference of sequence and the gray correlation coefficient. 

15. Calculating The Difference of Sequence

16. Calculating The Gray Correlation Coefficient This Photo by Unknown author is licensed under CC BY-SA .

17. Calculating The Gray Correlation Degree This Photo by Unknown author is licensed under CC BY . The g4j can be calculated as g4j = [0.61, 0.653, 0.703, 1] (j = 1, 2, 3,4). After normalized, the weight can be obtained: [W1, W2, W3, W4,] = [0.206, 0.220, 0.237, 0.337].

18. Reliability Improvement Feasible Index (RIFI) This Photo by Unknown author is licensed under CC BY .

19. Establishing The Models T i : Expenditures C: Lowest cost L i : the minimum reliability value that is 0.5. U i : The highest reliability value that is 0.95.

20. Result  

21.  Thank You   Prepared by : Rouna Hami  220000888090 This Photo by Unknown author is licensed under CC BY-SA .