# A Decision Model for Public Economic Environment Monitoring and Management Decision Using Improved Ant Colony Algorithm

Authors: Hongmei Ji; Zhuang Li
Journal: Journal of Environmental and Public Health
 (2022)

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## Abstract

The quality of economic development is not sufficient, despite the apparent role that public environmental monitoring and management play in the economy’s rapid expansion. Therefore, enhancing the standard of economic growth is of the utmost importance. It is vital to establish innovative management techniques to support social and governmental transformation in order to raise the standard of economic development. Economic development affects public administration’s fundamental duties and goals. The division of public administration distributes social resources and enhances the market’s function. The fundamental problem in public economic management is how to successfully actualize rational resource allocation, advance social justice, and boost social welfare on the basis of resource scarcity and the breakdown of the market mechanism. This study greatly increases the global optimization performance of the fundamental ant colony method and provides the explicit programme and simulation stages for the new algorithm. Finally, simulation tests are conducted using the basic ant colony algorithm and the upgraded ant colony algorithm in relation to the decision-making model of public economic management. According to the simulation findings, the revised algorithm successfully addresses the traditional approach’s drawbacks, including its slow convergence speed and propensity to easily enter local minima, and its optimization performance has increased by 30.23%.


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## Body

## 1. Introduction

The highest state and ultimate goal of public economic management is to achieve the best provision, best distribution, best exchange, and best consumption of public goods with the most economical resource input. It is actually a complex system or system composed of its subject and object, goal and means, principle and approach, system and mechanism, environment and resource, process and result, theory, and method [1]. Only through scientific design, rational construction and effective implementation of this complex system can the productive forces of the public economy be brought into full play and properly developed under the delicate organization [2]. The leader of public management is a public organization or a nongovernmental organization within the government. The leader needs to establish a correct and objective decision-making model according to the policy, so that the production relations of the public economy can be synergistically optimized under the correct treatment, so that the whole production mode of the public economy can run healthily, efficiently, and sustainably along a smooth rising track [3]. The essence of rational decision-making model is policy optimization, and the rational decision-making model of public policy analysis should not and cannot be the only tool and mode of actual public policy analysis.Recent developments in the disciplines of environmental quality assessment, weather forecasting, economic management, and teaching process evaluation have given rise to a type of fuzzy mathematics technique known as the decision model. However, with continued use in complex systems like the economy and society, problems’ complexity, and unpredictability as well as the ambiguity of human thought continue to grow, making it challenging for individuals to evaluate them with objectivity and come to judgments [4]. Any economic management decision-making issue, regardless of how straightforward or difficult, must meet the following four sorts of criteria: technologically sophisticated, economically rational, implementable, and policy-permitting. This decision-making model bases its conclusions on the supposition that people are rational, and it emphasizes the importance of people in the formulation of public policy [5]. Currently, performance is the main consideration in the creation of ant colony algorithms. This study examines the enhanced performance of the ant colony algorithm, suggests a new enhanced method, and evaluates it. The global combinatorial optimization problem serves as the foundation for this development. It is a new method, hybrid algorithm, to improve the ant colony algorithm strategically. This algorithm makes use of the advantages of different optimization algorithms to complement each other and makes overall strategy adaptive adjustment in the whole evolution mechanism of the algorithm, so as to optimize the performance of the public economic management decision-making model.The main body of public economic management should pay attention to the in-depth analysis of favorable factors and unfavorable factors in the internal environment and external environment and be good at actively improving the internal and external environment by formulating and implementing relevant public economic policies in a targeted manner [6]. Correctly handle internal and external conflicts, and strive to turn negative factors into positive factors, in order to improve management effects and achieve management goals [7]. Any management must choose and use corresponding methods, and public economic management is no exception. Methods of public economic management can be classified from different perspectives [8]. These various methods classified according to different angles intersect with each other, and different types of public departments have their own specific management methods [9]. Therefore, it is necessary to innovate and reshape it with the management doctrine with economy and efficiency as the core values and rebuild the process and mode of public management. The specific process of public economic management is the effective combination of resources and human resources for the economic activities within the functional scope of the public sector through planning, decision-making, organization, leadership, coordination, evaluation, and other links [10]. The innovation of this paper lies in the following:
(1)
The system management method based on overall coordination is proposed to guide the implementation of public economic management decisions. With this method, the guiding concept of overall coordination in public economic management can be strengthened. Through scientific organization and careful arrangement, ensure that the whole and parts (elements), the body and the external environment, the horizontal subsystems, and the vertical levels of each public institution always operate in a coordinated and orderly manner around the realization of the overall functional objectives(2)
From the perspective of practical application, a comprehensive decision model is proposed. In the model, we refer to the decision-making methods of large-scale systems and integrate the experience of many experts, so that the weights of the evaluation matrix and factors are expressed by positive bounded closed interval numbers, and a ranking method of interval numbers is given. Thus, a series of problems from theory to application of the model are completely solvedThis paper is divided into six sections from the organizational structure.The first section is the introduction, which points out that public management can promote the economy obviously, but the quality of economic development is not satisfactory. It is imperative to improve the quality of economic growth, which requires innovation of management mechanism and promotion of government transformation and social transformation. The second section is a summary of relevant literature, summarizing its advantages and disadvantages, and putting forward the research ideas of this paper. The third section analyzes the decision-making system and model printing of public economic management. The fourth section is the analysis and description of the improved ant colony algorithm. The fifth section discusses simulation analysis and simulation experiment of improved algorithm and experimental results. The sixth section shows research prospect and strategy analysis. The seventh section is the conclusion, summarizing the research results of the full text.


## 2. Related Work

Public economic management is a multidisciplinary comprehensive discipline, which includes not only the theoretical basic disciplines such as economics and management but also the background of sociology, ethics, law, and other disciplines. Looking at public economic management from different disciplinary perspectives, different concepts, and frameworks will be formed. Therefore, over the years, scholars have had a lot of controversy over the concept of public economic management.The deterministic global optimization method proposed by Tang and Wang is strict in mathematical theory, which is suitable for relatively simple or qualitatively studied global optimization problems, and it is difficult to obtain the global optimal solution [11]. And the ant colony algorithm is easier to realize. Such a fast, stable, and universal optimization algorithm is what people want. After studying many decision-making problems in real life that rely on psychological measurement, Kumar and Setunge found that these problems are mainly reflected in such a kind of estimation to estimate or evaluate the satisfaction of something to a certain goal or requirement from a certain angle. Therefore, their quantification is the key to model establishment [12]. Tahir et al. pointed out that under the new situation, the overall ability of the government, especially the economic management ability of the government, is the key to the success of an economy. The rapid change of economic environment has brought great challenges to public management [13]. Therefore, in general, the public economic management defined by Woschank et al. not only includes the management of the public sector’s own economic activities but also involves the regulation and regulation of macro and micro economic activities by the public sector with management authority. It is the unity of internal management and external regulation of the public sector [14]. Yi showed that public economic management is a “regulator” for correctly handling public economic production relations and achieving a harmonious state [15]. Zhang and Lu emphasized the need to introduce a new managerial responsibility mechanism in the public economy. In order to “reshape the government” and establish a “corporatized” management government, the public economic sector has introduced modern management technology, including the private sector’s business management law-strategic management, total quality management, and cost management and established a new managerial government responsibility mechanism [16]. In his research conclusion, Zhao aims to summarize the major progress made by western economic management experts and development economists in the discussion of public economic management theory in recent years and discusses the redefinition of public sector and the problems it faces, the improvement of public economic management ability, and the institutional pluralistic structure [17]. Tang et al. think that the return of the value of efficiency priority in traditional public administration has led to the wandering and confusion of the main body of public economic management in grasping the connotation of fair value and the choice of efficiency tools in the management process and even the inclination to efficiency first has appeared [18]. Therefore, later, scholar Peizhang strongly concluded that a complete and reasonable value system of public economic management must give consideration to both purposeful values and instrumental values [19]. Su et al. also suggested broadening the communication channels between the public and public administration departments, and constantly improving the mechanism of people’s interest expression, interest integration, and democratic supervision. Efforts should be made to explore and improve the mechanism of citizen participation and bring orderly citizen participation into the public decision-making process [20].


## 3. Construction of Decision Model System

The market economy is currently in a stage of rapid expansion and significant firms place a lot of emphasis on making economic decisions, which mostly concern profit margins, investments, inventory turnover, and total assets. Building a sound economic system, precisely analyzing the important content of economic benefits, developing appropriate decision-making models, and obtaining useful value information are all required in order to deal with economic decision-making scientifically and maximize economic benefits. The key to making decisions is to assess, pick out, and get rid of the poor. As a result, to carry out this activity, people construct a thorough evaluation system, which may be condensed into an organized hierarchical framework. We can use the pairwise comparison approach to evaluate and calculate the factors for any simple ordered hierarchical system in order to determine the ranking outcomes of the decision objects and, ultimately, to provide quantitative support for the decision-makers to make scientific conclusions, as shown in Figure1.Figure 1
Economic management decision-making system.In the process of economic growth, quantity often precedes quality. This is an extensive economic growth model. The ecological and social costs are too high. It is not because the market management mechanism is imperfect, which is not conducive to economic development. In addition, judging from the current economic situation, economic diversification is the main feature of economic development. The diversification of economic entities has led to fierce competition among various entities, and even some malicious competition has occurred, disrupting the market order and damaging the reputation of businesses. Therefore, the government should strengthen management and promote the steady development of the economy by innovating the management system, improving the efficiency of resource management, regulating the behavior of the main body, and changing the market order. Therefore, the task can be reasonably completed only when sufficient resources are allocated by the cloud system. However, on the basis of completing the task, we should optimize the implementation of the algorithm as much as possible, such as achieving fair distribution. Most of the traditional scheduling algorithms only consider the performance of the algorithm from a single level. As a result, there are issues with both the task’s difficulty and fairness of allocation. It is essential to make sure that users have equitable possibilities for resource selection and to choose resources as much as feasible based on task characteristics in order to increase user satisfaction. This will assure the fairness of business rivalry in the cloud environment. Based on the parallels at many layers above, it is possible to apply the decision-making model for social wealth distribution to the issue of resource allocation in the cloud environment, offering a fresh approach to task scheduling. Figure2 depicts the particular mapping relationship.Figure 2
Model projection under virtualization technology.The multiattribute decision-making problem with the decision-maker’s deterministic plan preference mainly depends on the decision-maker’s measurement and computing power. Since the preference value is definite, the optimal decision-making process only involves comparison and does not involve real judgment and selection with the uncertainty of the decision-making subject. Therefore, the research focus of such problems lies in the exploration of model data preparation and algorithm research. Therefore, there are higher requirements for the collection of decision makers’ data, the construction of methods, and the application level of practice.On the basis of decision-making information, the specific method of weighing multiattribute is generally based on the quantitative attribute evaluation value normalized by attribute weight. Under the background of sustainable development of regional economic growth, while pursuing the maximization of economic benefits, investment must also consider social benefits, environmental benefits, and other objectives. In the decision-making process, goals such as profit are required, and the minimum cost, the best quality, and the maximum profit are required. The trade-off of decision-makers in multiattribute decision-making is to use the subjective preferences expressed by individuals, to construct the benefit function by mathematical methods, and to consider the combination of attributes to carry out the trade-off.


## 4. Algorithm Analysis and Description

Currently, the ant colony algorithm uses one type of pheromone update rule that is only used globally and the other type that uses both local update rule and global update rule. The test reveals that the two update rules cannot produce better outcomes when applied simultaneously. The results, on the other hand, show that the quality of the optimization results has declined. This is due to the fact that each ant makes a circle before releasing pheromones along its own path. The more valuable the information the ants get as they are moving, the more likely they are to choose the course taken by other ants, and the more closely the ants cooperate with one another;nij is its heuristic function:
(1)ηij=1dijχ1.Obviously, this heuristic function expresses the expected degree of ants transferring from element to another element.The information that was previously present eventually fades away with time; hence, in everyn moments, the number of local pheromones between two element states should be changed using the following formula:
(2)ψij=T+n=1−γ∗ϑijn=ω∗λ0,(3)λ0=1nTmin.The ant colony algorithm is a metaheuristic algorithm and includes various parameters. Although the introduction covered the choice of these parameters, many particular cases will require a different choice of parameters. Although, in theory, the choice of parameters will have a direct impact on the algorithm’s performance and convergence, the heuristic approach also benefits from variable parameter setup. The modified ant colony algorithm’s best algorithm parameter group is displayed in Table1.Table 1
The influence of each participant of the improved ant colony algorithm on the performance of the algorithm.
abcφσOptimal path length0.30.30.40.40.44690.50.20.50.40.54820.50.50.40.20.14070.40.30.20.10.14350.50.40.40.10.34220.10.20.20.40.1416Now, this model is further extended to introduce index matrix, index membership function, index membership matrix, and index dimensionless correction matrix. The following is the deviation consistency index of the judgment matrix:(4)CI=λmax−nn+1,(5)λmax=1n∑i=1nT2.In the formula,λmax is the largest eigenvalue of the judgment matrix.It is generally believed that when the CR is about 10%, the judgment matrix has satisfactory consistency. After this value is exceeded, the judgment matrix must be adjusted to have satisfactory consistency. Practice and theory have proved that as long as the evaluation indexes can be quantified; the CR results show that the judgment matrix is highly consistent.Based on the above evaluation function of the fairness of the single task assignment result, we can judge the fairness of the overall assignment result of the system. If the task set in the cloud system is represented asT=T1,T2,⋯,Tn and the corresponding resource allocation result evaluation is represented as R=R1,⋯,Rn, then, the fairness of the system is defined as
(6)J=∑i=1nαTi+1.In the formula, whenJ takes the minimum value, it means that the system achieves the fairness of each user to the greatest extent.Pheromone is a chemical used by ants to communicate. Each ant leaves a certain quantity of pheromone along its path, and over time, this pheromone gradually deteriorates. The quantity of leftover information on the trail can be used by succeeding ants to detect this pheromone and control their activity. The likelihood of choosing the more informed path is higher. Various ants may choose different paths simultaneously throughout the path selection process. As a result, the optimization method offers great qualities like parallelism and robustness. The only ants with the ability to make global modifications are those who have created the global ideal solution. The guidelines for global adjustment are(7)λij=t+n=1−β∗λijt+β∗Δλij,(8)Δλij=∑i=1mΔδit∗n.Among them,β is the volatility coefficient. Δλij represents the increment of the number of pheromones on path ij in this cycle.Obviously, the more ants, the better the algorithm’s ability to perform global searches, but this will reduce the algorithm’s rate of global convergence. As a result, when there are many ants, two ants from both ends replace one ant in the search for set items. The global convergence of the algorithm can be greatly enhanced by this parallel processing approach. The current answer is replaced with the outcome of the first iteration if it is superior to the previous iteration’s best result. The ant should then update the pheromones of each node it passes over before the following iteration, specifically:(9)∏mnt+1=1−σ∏mnt+Δ∏mnt,(10)Δtmnt=QCk.δ is the volatile coefficient of pheromone. 1‐δ is the residual factor of pheromone, and Πmnt is the pheromone increment of supply chain nodes in this cycle. Q is the pheromone strength, which affects the convergence speed of the algorithm to some extent. The ant colony algorithm adopts pheromone mechanism, which accelerates the convergence of the algorithm to the optimal solution. Obviously, every time a complete process of task scheduling and resource allocation is completed, the pheromone values on related virtual machines need to be updated.


## 5. Improved Algorithm Simulation Analysis and Simulation Experiment

This study is aimed at identifying the ideal number of iterations for the enhanced ant colony method. This study compares the average task completion times of tasks produced by the enhanced ant colony algorithm after various iterations under the assumption of a specific model structure and a predetermined number of tasks.From the performance test chart of the local optimization algorithm, it is found that the application of this algorithm can achieve higher satisfaction with fewer iterations and has better performance than the exhaustive calculation method. The test is divided into two cases: the number of ants isX1 and x2. From Figure 3, it can be seen that the performance curve with the number of ants is higher than the performance curve with the number of ants is x2. This is because when the number of ants is large, there are many paths to search once, and the satisfaction value corresponding to the iteration has a large jump. Because better services are randomly selected, the performance has been significantly improved.Figure 3
The best point simulation process.The scatter distribution in Figure4 shows that the experimental findings are unstable and the basic ant colony method has a poor success rate. Because the method converges to the local optimal solution earlier and causes the programme to stagnate, the success rate curve does not clearly grow as the number of iterations increases. By comparing the results in Figures 3 and 4, we can see that it takes 2500 iterations to reach the maximum satisfaction in Figure 4, calculated according to the curve with the number of ants of 100 and 250 calculations, 50 calculations, 500 calculations, and 1000 calculations for the traditional algorithm.Figure 4
Local optimization algorithm performance test.In the ant colony algorithm, the ants choose the service with more pheromone with a certain probability, which means that this is a better service. Through such a positive feedback mechanism, more and more ants will choose better services and find the best services in the global scope. Since the pheromone intensityQ is a constant characterizing the number of trajectories left by the ants, it affects the global convergence speed of the algorithm. If the value is too large, the algorithm will converge to the local minimum. If it is too small, the global convergence speed will slow down. When there are many elements in the set index a, if the volatility coefficient is too large, the global search ability of the algorithm will be reduced. If the coefficient decreases, the global search ability of the algorithm will be improved, but the convergence speed will be slow. An adaptive control strategy can be adopted for the volatilization coefficient; that is, the initial value can be large. With the continuous increase of the number of cycles, if the optimal values of each time are not different, it indicates that the process has fallen into a certain extreme point, which is not necessarily the global optimal solution. Figure 5 is a comparison of the performance test of local optimization algorithms under different pheromone strengths.Figure 5
Performance test of improved ant colony algorithm local optimization algorithm.Then, in order to verify the solution of the improved ant colony algorithm in different problem models, two groups of scale parameters are set. In the experiment, two kinds of implementations are used to represent the trend. The algorithm parameters are set unchanged, and the results obtained by running 20 times independently are shown in Figure6.Figure 6
Algorithm optimization under different scales.To sum up, a series of improvement strategies proposed in this paper have significantly improved the global optimization speed of the basic ant colony algorithm and effectively overcome the shortcomings of slow convergence speed and easy to fall into the local minimum point of the algorithm, and the optimization performance of the algorithm has been improved by 30.23%.Finally, based on the perspective of multivariate statistical analysis, the model simulation experiment is carried out. Through the investigation of the end-user satisfaction, analyze the shortcomings in the social and economic system structure, correct the mistakes and omissions in the early market demand investigation, and timely discover the market development trend and user tendency. Integrate products and form complete and mature industry solutions, adjust operation strategies and means, formulate short-term, medium-term, and long-term development plans, and improve their market competitiveness. Increase investment in capital and operation for key products, timely analyze the products with problems, and reasonably adjust the operation planning, construction, and upgrading plan, so as to reduce the investment cost and improve the social and economic benefits (see Table2 decision calculation table).Table 2
Comprehensive decision-making calculation table and conclusion.
ProgrammeABCDEFTechnologyExpert0.130.120.10.150.190.17The masses0.150.170.170.160.160.14Government0.10.180.170.110.110.19EconomyScale0.140.170.150.170.180.12Invest0.130.140.120.130.180.11Financial capacity0.150.120.190.110.110.18PolicyIndustrial policy0.120.130.140.140.160.11Tax policy0.110.170.130.10.10.11Loan policy0.110.10.170.20.150.12Derived from Table2, the weights of the evaluation indicators of different decision-making model schemes (described in Figure 7) change the traditional way of allocating funds by the current base method, actively explore new scientific and effective methods of fund allocation, and reduce the subjectivity and randomness of fund arrangements. And strengthening the use of supervision and performance evaluation is an effective method of public economic management. As a complex giant system with multidepartments and multilevels, public economy’s operation efficiency and function are dominated by the two system principles of division of labor and cooperation and “short board restriction.” Therefore, a fundamental condition to ensure that the positive functions of the public economy can be brought into full play is to make full use of the system management method based on overall coordination in management.Figure 7
Weights of evaluation indicators for different decision-making models.In the process of economic management, the attributes of data are mostly continuous values. In order to approximate them, they are discretized first. Considering that in the process of public policy implementation, each variable is basically set with upper and lower limits; the attribute variable is discretized into three states (low, normal, and super high) according to the set value, which are, respectively, brought into scheme 1-4 for simulation, and a discrete decision table is established to replace the continuous decision table. The clear matrix of the decision table is obtained according to the definition, and then, the clear function is obtained. The clear function is reduced to several disjunctive forms of conjunction, and each conjunction in the disjunctive form corresponds to a result of conditional attribute reduction.The establishment of the decision-making model needs to gradually deepen the investigation and analysis of economic management, orderly carry out the collection, sorting and summary of economic operation laws, extract valuable information, help economic decision makers provide reference opinions, put forward specific reform methods and guiding measures, promote public management and economic distribution, and make the national economy develop steadily.


## 6. Optimization Strategy of Decision-Making Model for Public Economic Management

In order to significantly overcome the limitations of both market failure and government failure, the functional orientation of public economic management should not aim at comprehensively controlling the entire economic operation. Instead, it should seek the rational division of labour, coordination and cooperation, and complementary advantages between the public sector and the market. The goal of public economic management needs to be based on drawing a line between the public and private sectors that is both rational and based on science. Based on this, we should encourage the two’s harmonious interaction, work to promote economic growth, price stability, full employment, and balance of payments in order to facilitate the development of a fair, just, open, inclusive, and sustainable economic and social development model and ultimately establish joint governance of the public sector. Therefore, the decision-making model for public economic management can be optimized by making acceptable improvements to the following factors.(1)
Change the governance mode, and improve and innovate the management system. The economic operation competition mechanism shall be introduced into the market, and the main role of the market in resource allocation shall be brought into play. Improve the transparency of the operation of rights and the handling of affairs, strengthen social supervision and participation, and establish and improve a supervision and coordination mechanism in which each department performs its own duties, cooperates closely, cooperates with each other, and jointly manages, so as to effectively reduce costs and improve efficiency(2)
In the result-oriented performance management method, the performance objectives of each public department, each public institution, and even each public expenditure project and each public servant’s post are defined in advance, and the quantitative evaluation indicators that accurately evaluate the degree of achievement of these performance objectives are formulated as the basis for the implementation of process control during the planning period(3)
Establish a monitoring, evaluation, and feedback mechanism. Use appropriate supervision means to test and correct the behaviors of implementing policy objectives, standardize various management activities within the scope permitted by the policy, prevent and correct policy implementation deviations, and protect their legitimate rights and interests


## 7. Conclusion

Therefore, the theoretical research and specific practice of public economic management should not only apply the general theory and experience of economic management but also conduct independent exploration in combination with the special internal relations of public economy, so as to understand and grasp the essence and laws of public economic management in the combination of general and special, so as to achieve the objectives of public economic management. Changing the way of social governance, improving, and innovating the management system are important parts of promoting government reform and the transformation of government functions and improving the quality of economic growth. It also saves the cost of government operation and market transactions, so as to realize effective and reasonable resource allocation and various ways of management system innovation. In the unpredictable economic changes and social conflicts, whether the public economic policy can timely resolve the contradictions and obstacles in economic and social development is an urgent problem for the government. The formation of public economic policy is a complex dynamic process. The dynamic and complexity of its practice determine the randomness and complexity of the public policy model. Under different historical backgrounds and different political and economic systems, the decision-making model of public policy will also change accordingly. We cannot generally say which model is more useful. We should use a variety of decision-making models as tools to conduct multidimensional analysis of public policy.



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