Big Data Optimization and Applications in Running Efficiency of Higher Education

The world is undergoing great changes that have not been seen at present; colleges and universities can only adapt to social development with a more active and open attitude. Meanwhile, colleges and universities strive to obtain more social resources during the process of gradually embedding social funds into the operation system of universities. In such a backdrop, we establish an optimization model for university running efficiency under limited funds, where the objective function is quadratic and restraint condition is linear. With the help of optimization theory, we have obtained the optimal solution of this optimization model and put forward corresponding suggestions to improve the running efficiency of higher education.

Encroachment in a three-echelon supply chain: manufacturer encroachment or distributor encroachment

PurposeThe purpose of this paper is to investigate manufacturer encroachment and distributor encroachment in a three-echelon supply chain consisting of an upside manufacturer, an intermediate distributor and a downside retailer.Design/methodology/approachIn this paper, the authors use the optimization theory to mathematize the proposed question and build a model. First, the authors consider sequential quantity decisions, where the encroacher decides on the direct selling quantity after determining the retailer's order quantity. Second, the authors relax this sequential decision process assumption by reconsidering a circumstance in which quantity decisions are decided simultaneously.FindingsIn contrast to previous studies, this study shows that in three-echelon supply chains, the upside firm is more likely to encroach compared with the downside firm. The “bright side” of encroachment exists for all players only when the encroachment cost is at a moderate level. However, in manufacturer encroachment under simultaneous quantity decisions, the “bright side” skips the distributor but benefits the retailer directly as the encroachment cost increases from zero to a certain level. The main reason lies in that the distributor loses its pricing power because the end-market has been disturbed by the simultaneous quantity decisions. A comparison of the results of sequential and simultaneous quantity decisions reveals the merit of simultaneous quantity decisions. The authors find that the intermediate role (the distributor in our model) in three-echelon supply chains may benefit more from simultaneous quantity decisions. That is, the distributor may achieve a better profit even in a market with intensified competition.Originality/valueThe findings of this paper contribute to the marketing science literature on encroachment. The majority of existing literature has focused on manufacturer encroachment in two-echelon supply chains. This paper innovatively investigates and compares manufacturer encroachment and distributor encroachment in a three-echelon supply chain.

The Mechanism for Effectively Meeting the Needs of the Population in Essential services by Regions Municipal Economy: Current State and Trends

The importance of effectively meeting the needs of the region's population in essential services under conditions of uncertainty is becoming an increasingly important and relevant area of economic development of the local economy. A systematic study carried out in the article pertaining to assessing and using the potential of interaction between the state, regions and municipalities in order to meet the needs of the population in essential services contributes to strengthening the capabilities of the local economy. But this cannot be achieved without analyzing the external and internal environment and implementing, on this basis, a forecast of a dynamic change in the economic situation, to which the power structures do not pay due attention. It was found that the shortcomings of the methodological tools lead to a low quality of the developed forecast and management decisions. The article clarifies the concept of strategic management in relation to the socio-economic development of territories, shows that solving such problem situations increases the potential of the local economy, aims at increasing efficiency and has a positive effect on strengthening the socio-economic potential of the Siberian territories. Proposals aimed at solving the problems of forecasting socio-economic development have been prepared. It is shown that the mechanism of work of state structures of territories and of business on the field of rendering socially important services to the population, based on the use of optimization theory in forecasting activity, allows to reveal unused opportunities and redistribute them in the areas being the bottlenecks. The proposals include a conceptually distributed in time optimization model of effective solutions to meet the needs of the population in the region in services based on the real state of the economy and the emerging prospects for dynamic change towards growth. This view of the problems of the local economy makes it possible to use the proposed organizational and economic solutions to the challenges with a high degree of efficiency. This stimulates the search for new approaches to the study of the problems faced by municipalities, the identification of relevant forms and methods of solving socially significant problems.

An example to illustrate several aspects of optimization theory in Managerial Economics

We provide a single example that illustrates all aspects of linear, integer and dynamic programming, including such concepts such as value of perfect and imperfect information. Such problems, though extremely plausible and realistic are hardly ever discussed in managerial economics.

Two-Stage Robust Optimization Model for Uncertainty Investment Portfolio Problems

Investment portfolio can provide investors with a more robust financial management plan, but the uncertainty of its parameters is a key factor affecting performance. This paper conducts research on investment portfolios and constructs a two-stage mixed integer programming (TS-MIP) model, which comprehensively considers the five dimensions of profit, diversity, skewness, information entropy, and conditional value at risk. But the deterministic TS-MIP model cannot cope with the uncertainty. Therefore, this paper constructs a two-stage robust optimization (TS-RO) model by introducing robust optimization theory. In case experiments, data crawler technology is used to obtain actual data from real websites, and a variety of methods are used to verify the effectiveness of the proposed model in dealing with uncertainty. The comparison of models found that, compared with the traditional equal weight model, the investment benefits of the TS-MIP model and the TS-RO model proposed have been improved. Among them, the Sharpe ratio, Sortino ratio, and Treynor ratio have the largest increase of 19.30%, 8.25%, and 7.34%, respectively.

Optimal Port Design Minimizing Standing Waves with A Posteriori Long Term Shoreline Sustainability Analysis

Optimization theory is applied to a coastal engineering problem that is the design of a port. This approach was applied to the redesign of La Turballe Port in order to increase the exploitable surface area and simultaneously reduce the occurrence of long waves within the port. Having defined the cost function as a weighted function of wave amplitude and with the chosen parameterization of the port, results show that an extended jetty and a widened mole yield a unique optimal solution. This work demonstrates that numerical optimization may be quick and efficient in the identification of port solutions consistent with classic engineering even in the context of complex problems.

The problem of optimizing the schedule of perishable agricultural products processing

Subject. The article addresses the economic, scientific, technological, and production activities of processing plants within the agri-industrial complex. Objectives. The study aim to analyze and describe the specifics of storing perishable agricultural products, and the impact on both the further processing and final results of a processing enterprise. Methods. We employ methods of analysis and synthesis, grouping and comparison, abstraction, generalization, and analogy. We provide a mathematical model that describes the sugar beet processing, taking into account the level of sugar content, based on methods of mathematical modeling and optimization theory. Results. Our analysis of the influence of storage time of perishable agricultural products on their further processing showed that this factor can have a serious impact on the results of processing enterprises. We investigated the issue, using the case of such an important technical culture as sugar beet. We highlight an important factor, which can significantly improve the results of economic activity of enterprises, i.e. the formation of a schedule for the order of processing of sugar beet with different levels of sugar content. Conclusions. To maximize the final output, the sugar beet processing should start with batches of maximum sugar content. We provide assessments, characterizing the level of final output, should this rule be violated. The findings may serve as a basis for developing more general mathematical models, which describe the sugar beet processing and consider other factors, including the dynamics of the process of beet pile fields replenishment with sugar beet of various sugar content.

Research on a Bi-Level Collaborative Optimization Method for Planning and Operation of Multi-Energy Complementary Systems

Multi-energy complementary systems (MCSs) are complex multilevel systems. In the process of system planning, many aspects—such as power planning, investment cost, and environmental impact—should be considered. However, different decision makers tend to have different levels of control objectives, and the multilevel problems of the system need to be solved effectively with comprehensive judgment. Therefore, based on the terminal MCS energy structure model, the optimization method of MCS planning and operation coordination, considering the influence of planning and operation in the system’s life cycle, is studied in this paper. Consequently, the research on the collaborative optimization strategy of MCS construction and operation was carried out based on the bi-level multi-objective optimization theory in this paper. Considering the mutual restraint and correlation between system construction and operation in practical engineering, a bi-level optimization model for collaborative optimization of MCS construction and operation was constructed. To solve the model effectively, the existing non-dominated sorting genetic algorithm III (NSGA-III) was improved by the authors on the basis of previous research, which could enhance the global search ability and convergence speed of the algorithm. To effectively improve and strengthen the reliability of energy supply, and increase the comprehensive energy utilization of the system, the effects of carbon transaction cost and renewable energy penetration were considered in the optimization process. Based on an engineering example, the bi-level model was solved and analyzed. It should be noted that the optimization results of the model were verified to be applicable and effective by comparison with the single-level multi-objective programming optimization. The findings of this paper could provide theoretical reference and practical guidance for the planning and operation of MCSs, making them significant for social application.