Operational preparation: the answer to the question of principles, tools and applications of xiao yongbo is one of the disciplines to study how best to make decisions under resource constraints, including principles, tools and applications. These three areas will be addressed in this paper, with relevant references. 1. Rationale of operational preparation: the core principle of operational preparation is:Optimizing theoryThese include, inter alia, linear planning, integer planning, dynamic planning, network flow, decision theory, etc. Of these, linear planning is the most commonly used method of operational preparation, and its mathematical model can be expressed as a series of linear bindings under the goal function of maximizing (or minimizing) the target. Integer planning, on the other hand, is an extension of linear planning, limiting decision variables to integers and applying them to actual decision-making issues. Dynamic planning, in turn, applies to issues that require consideration of the shift in status and optimal sub-structure. Network flows are used to address the issues of the shortest circuits and the smallest tree generation in the network. Decision-making theory is an extension of operational preparation under uncertain conditions, including methods such as risk decision-making, decision tree etc. References: books: 1) principles and methods of preparatory processes (fourth edition), author: silver city, lin 2) linear planning and network flows (third edition), author: xiaofeng 3, dispersional optimization issues (second edition), author: high 2. Instrument for preparatory processes: tools for preparation include mathematical modelling, optimization of algorithms and decision support systems (dss). Mathematic modelling is the process of abstracting practical problems into mathematical models, and it is the basis for operational applications. Optimizing algorithms is the solution to mathematical models, which often include simple form, internal point method, genetic algorithms, simulated regression algorithms, etc. Decision support systems are tools that combine operational methods with information technology and are designed to assist decision makers in decision-making. It can help policy makers to analyse problems, choose options and assess risks, and improve the scientificity and efficiency of decision-making. Relevant
