A State Transition Algorithm with Variable Local Candidate Solution Space and its application to Residue Hydrogenation Fractionation Process

Author(s):  
Kemin Yi ◽  
Yalin Wang ◽  
Bei Sun ◽  
Sun Jiazhou
2022 ◽  
Vol 205 ◽  
pp. 107707
Author(s):  
Tengfei Zhang ◽  
Defeng Wu ◽  
Lingyu Li ◽  
Andre S. Yamashita ◽  
Saifeng Huang

2019 ◽  
Vol 36 (06) ◽  
pp. 1940014
Author(s):  
Qi Zhang ◽  
Jiaqiao Hu

We propose a random search algorithm for seeking the global optimum of an objective function in a simulation setting. The algorithm can be viewed as an extension of the MARS algorithm proposed in Hu and Hu (2011) for deterministic optimization, which iteratively finds improved solutions by modifying and sampling from a parameterized probability distribution over the solution space. However, unlike MARS and many other algorithms in this class, which are often population-based, our method only requires a single candidate solution to be generated at each iteration. This is primarily achieved through an effective use of past sampling information by means of embedding multiple nested stochastic approximation type of recursions into the algorithm. We prove the global convergence of the algorithm under general conditions and discuss two special simulation noise cases of interest, in which we show that only one simulation replication run is needed for each sampled solution. A preliminary numerical study is also carried out to illustrate the algorithm.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaojun Zhou ◽  
Jianpeng Long ◽  
Chongchong Xu ◽  
Guanbo Jia

This paper proposes an external archive-based constrained state transition algorithm (EA-CSTA) with a preference trade-off strategy for solving the power dispatch optimization problem in the electrochemical process of zinc (EPZ). The optimal power dispatch problem aims to obtain the optimal current density schedule to minimize the cost of power consumption with some rigorous technology and production constraints. The current density of each production equipment in different power stages is restricted by technology and production requirements. In addition, electricity price and current density are considered comprehensively to influence the cost of power consumption. In the process of optimization, technology and production restrictions are difficult to be satisfied, which are modeled as nonconvex equality constraints in the power dispatch optimization problem. Moreover, multiple production equipment and different power supply stages increase the amount of decision variables. In order to solve this problem, an external archive-based constrained state transition algorithm (EA-CSTA) is proposed. The external archive strategy is adopted for maintaining the diversity of solutions to increase the probability of finding the optima of power dispatch optimization problem. Moreover, a preference trade-off strategy is designed to improve the global search performance of EA-CSTA, and the translation transformation in state transition algorithm is modified to improve the local search ability of EA-CSTA. Finally, the experimental results indicate that the proposed method is more efficient compared with other approaches in previous papers for the optimal power dispatch. Furthermore, the proposed method significantly reduces the cost of power consumption, which not only guides the production process of zinc electrolysis but also alleviates the pressure of the power grid load.


2019 ◽  
Vol 26 (7) ◽  
pp. 1910-1920 ◽  
Author(s):  
Jin-tian Yin ◽  
Yong-fang Xie ◽  
Zhi-wen Chen ◽  
Tao Peng ◽  
Chun-hua Yang

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