Dynamic planning method of economic operation optimization model

2020 ◽  
Author(s):  
Jing Jing
Keyword(s):  
Optimization Model ◽  
Planning Method ◽  
Dynamic Planning ◽  
Operation Optimization ◽  
Economic Operation

scholarly journals Operation Optimization of Natural Gas Transmission Pipelines Based on Stochastic Optimization Algorithms: A Review

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Xia Wu ◽  
Changjun Li ◽  
Yufa He ◽  
Wenlong Jia
Keyword(s):  
Natural Gas ◽  
Stochastic Optimization ◽  
Optimization Model ◽  
Optimization Algorithms ◽  
Optimization Models ◽  
Stochastic Algorithms ◽  
Operation Optimization ◽  
Natural Gas Pipelines ◽  
Computation Efficiency ◽  
Stochastic Optimization Algorithms

Operation optimization of natural gas pipelines has received increasing attentions, due to such advantages as maximizing the operating economic benefit and the gas delivery amount. This paper provides a review on the most relevant research progress related to the steady-state operation optimization models of natural gas pipelines as well as corresponding solution methods based on stochastic optimization algorithms. The existing operation optimization model of the natural gas pipeline is a mixed-integer nonlinear programming (MINLP) model involving a nonconvex feasible region and mixing of continuous, discrete, and integer optimization variables, which represents an extremely difficult problem to be solved by use of optimization algorithms. A survey on the state of the art demonstrates that many stochastic algorithms show better performance of solving such optimization models due to their advantages of handling discrete variables and of high computation efficiency over classical deterministic optimization algorithms. The essential progress mainly with regard to the applications of the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Simulated Annealing (SA) algorithms, and their extensions is summarized. The performances of these algorithms are compared in terms of the quality of optimization results and the computation efficiency. Furthermore, the research challenges of improving the optimization model, enhancing the stochastic algorithms, developing an online optimization technology, researching the transient optimization, and studying operation optimization of the integrated energy network are discussed.

scholarly journals Optimal Collision-Free Grip Planning for Biped Climbing Robots in Complex Truss Environment

2018 ◽  
Vol 8 (12) ◽  
pp. 2533 ◽  
Author(s):  
Shichao Gu ◽  
Haifei Zhu ◽  
Hui Li ◽  
Yisheng Guan ◽  
Hong Zhang
Keyword(s):  
Path Planning ◽  
Optimization Model ◽  
Mathematic Model ◽  
Planning Method ◽  
Climbing Robot ◽  
Climbing Robots ◽  
Kinematic Constraint ◽  
Anchor Points ◽  
Effectiveness And Efficiency ◽  
Original Point

Biped climbing robots (BiCRs) can overcome obstacles and perform transition easily thanks to their superior flexibility. However, to move in a complex truss environment, grips from the original point to the destination, as a sequence of anchor points along the route, are indispensable. In this paper, a grip planning method is presented for BiCRs generating optimal collision-free grip sequences, as a continuation of our previous work on global path planning. A mathematic model is firstly built up for computing the operational regions for negotiating obstacle members. Then a grip optimization model is proposed to determine the grips within each operational region for transition or for obstacle negotiation. This model ensures the total number of required climbing steps is minimized and the transition grips are with good manipulability. Lastly, the entire grip sequence satisfying the robot kinematic constraint is generated by a gait interpreter. Simulations are conducted with our self-developed biped climbing robot (Climbot), to verify the effectiveness and efficiency of the proposed methodology.

scholarly journals Cost minimization and operation optimization model for strategic waste management decision plans: A case study

2021 ◽  
Vol 15 (2) ◽  
pp. 98-108
Author(s):  
U. Babalola Faith ◽  
O. Adelopo AbdulGaniyu ◽  
M. Aiyepola Boluwatito ◽  
T. Nubi Afolasade
Keyword(s):  
Waste Management ◽  
Optimization Model ◽  
Cost Minimization ◽  
Management Decision ◽  
Operation Optimization
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