A COMPARATIVE STUDY OF HEURISTIC OPTIMIZATION ALGORITHMS

Heuristic optimization algorithms are of great importance for reaching solutions to various real world problems. These algorithms have a wide range of applications such as cost reduction, artificial intelligence, and medicine. By the term cost, one could imply that that cost is associated with, for instance, the value of a function of several independent variables. Often, when dealing with engineering problems, we want to minimize the value of a function in order to achieve an optimum, or to maximize another parameter which increases with a decrease in the cost (the value of this function). The heuristic cost reduction algorithms work by finding the optimum values of the independent variables for which the value of the function (the “cost”) is the minimum. There is an abundance of heuristic cost reduction algorithms to choose from. We will start with a discussion of various optimization algorithms such as Memetic algorithms, force-directed placement, and evolution-based algorithms. Following this initial discussion, we will take up the working of three algorithms and implement the same in MATLAB. The focus of this report is to provide detailed information on the working of three different heuristic optimization algorithms, and conclude with a comparative study on the performance of these algorithms when implemented in MATLAB. In this report, the three algorithms we will take in to consideration will be the non-adaptive simulated annealing algorithm, the adaptive simulated annealing algorithm, and random restart hill climbing algorithm. The algorithms are heuristic in nature, that is, the solution these achieve may not be the best of all the solutions but provide a means to reach a quick solution that may be a reasonably good solution without taking an indefinite time to implement.

A STUDY ON REGIONAL CIRCULAR ECONOMY SYSTEM AND ITS CONSTRUCTION, OPERATION AND SUGGESTION FOR SHANGHAI

The characteristics of the traditional linear economic model are high consumption, high emission and low efficiency. Economic development is still largely at the expense of the environment and requires a natural resource investment. This can realize rapid economic development but resource depletion and environmental pollution become increasingly serious. In the 1990's a new economic model, circular economics, began to enter our vision. The circular economy maximizes production and minimizes the impact of economic activities on the ecological environment through organizing the activities through the closed-loop feedback cycle of "resources - production - renewable resource". Circular economy is a better way to solve the contradictions between the economic development and resource shortages. Developing circular economy has become the major strategic initiatives to achieving sustainable development in countries all over the world. The evaluation of the development of circular economics is a necessary step for regional circular economy development. Having a quantitative evaluation of circular economy can better monitor and reveal the contradictions and problems in the process of the development of recycling economy. This thesis will: 1) Create an evaluation model framework and new types of industries and 2) Make an evaluation of the Shanghai circular economy currently to analyze the situation of Shanghai in the development of circular economy. I will then propose suggestions about the structure and development of Shanghai circular economy.