Research And Application Of Thermodynamic Genetic Algorithm

Thermodynamics is mainly from the perspective of energy conversion to study the thermal properties of matter, revealing the energy converted from one to another.Thermodynamics is the summary of the theory obtained from the macro-phenomenon of the substances and don’t involve the microscopic structure and the interaction of the particles, Thus, thermodynamics is a phenomenological macroscopic theory. With considerable reliability and universality.Entropy changes and the size specified the direction of thermodynamic processes and to reflect the stability of the system.According to the laws of thermodynamics, the temperature is kept constant and heat exchange with the surrounding environment closed system, the system free energy is always spontaneous changes in the direction of reduced, when the system is stable, the system free energy minimization.Therefore, the groups in genetic algorithm as a thermodynamic system, introduced in the optimization of energy, temperature, and the concept of entropy through the simulation of thermodynamic entropy and energy competition to quantify the coordination and optimization to improve the selection pressure and maintain Based on this understanding, committed to the thermodynamic and genetic algorithm combination used to solve the constrained single-objective optimization problem, constrained multi-objective optimization problem, and used to solve the scheduling problem of large-scale emergencies emergency supplies,our work is as follows:(l)By the free energy minimization principle in thermodynamic system, designed the framework of the algorithm based on the thermodynamic operation, the genetic algorithm used to solve single-objective optimization problem of thermodynamics, and numerical experiments to prove the validity of the algorithm.(2) inspired by the competition between entropy and energy of the thermodynamic system is designed thermodynamic hybrid genetic algorithm for solving constrained multi-objective function optimization problems, Through the design of thermodynamics operator to maintain a balance between population diversity and approximation, through the early elitist selection strategy to improve the quality of the initial population, the use of layered niche technology selection strategy, and finally through experiments on the effectiveness of the algorithm.(3) emergency items in short supply in the event of large-scale emergencies, the actual arrangements to minimize time and cost of emergency items, a reasonable allocation between the various manufacturers, in order to quickly economic transported to the affected areas through the establishment of the model, using a hybrid genetic algorithm for constrained multi-objective optimization of the thermodynamic calculation, experiments show that the algorithm validity.