Modeling and optimization for oil well production scheduling

In this paper,an oil well production scheduling problem for the light load oil well during petroleum field exploitation was studied.The oil well production scheduling was to determine the turn on/off status and oil flow rates of the wells in a given oil reservoir,subject to a number of constraints such as minimum up/down time limits and well grouping.The problem was formulated as a mixed integer nonlinear programming model that minimized the total production operating cost and start-up cost.Due to the NP-hardness of the problem,an improved particle swarm optimization(PSO) algorithm with a new velocity updating formula was developed to solve the problem approximately.Computational experiments on randomly generated instances were carried out to evaluate the performance of the model and the algorithm's effectiveness.Compared with the commercial solver CPLEX,the improved PSO can obtain high-quality schedules within a much shorter running time for all the instances.

Global Convergence of a New Restarting Three Terms Conjugate Gradient Method for Non-linear Optimizations

在这笔记，由把 PR 和 HS 方法的好数字表演与 FR 方法的全球集中性质相结合，新重启的一个班三项条款结合坡度方法被介绍。有二种普通的线搜索的新方法的全球集中性质被证明。