Improving Differential Evolution with Ring Topology-Based Mutation Operators

2014 ◽  
Author(s):  
Jingliang Liao ◽  
Yiqiao Cai ◽  
Yonghong Chen ◽  
Tian Wang ◽  
Hui Tian
Keyword(s):  
Differential Evolution ◽  
Ring Topology ◽  
Mutation Operators

scholarly journals Sufficient Conditions for Global Convergence of Differential Evolution Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Zhongbo Hu ◽  
Shengwu Xiong ◽  
Qinghua Su ◽  
Xiaowei Zhang
Keyword(s):  
Differential Evolution ◽  
Infinite Product ◽  
Differential Evolution Algorithm ◽  
Sufficient Conditions ◽  
Common Mutation ◽  
Convergence Conditions ◽  
De Algorithm ◽  
Mutation Operators ◽  
Evolution Algorithm ◽  
Algorithm Framework

The differential evolution algorithm (DE) is one of the most powerful stochastic real-parameter optimization algorithms. The theoretical studies on DE have gradually attracted the attention of more and more researchers. However, few theoretical researches have been done to deal with the convergence conditions for DE. In this paper, a sufficient condition and a corollary for the convergence of DE to the global optima are derived by using the infinite product. A DE algorithm framework satisfying the convergence conditions is then established. It is also proved that the two common mutation operators satisfy the algorithm framework. Numerical experiments are conducted on two parts. One aims to visualize the process that five convergent DE based on the classical DE algorithms escape from a local optimal set on two low dimensional functions. The other tests the performance of a modified DE algorithm inspired of the convergent algorithm framework on the benchmarks of the CEC2005.

scholarly journals Optimization of truck allocation in open pit mines using differential evolution algorithm

2021 ◽  
Vol 9 (8) ◽  
pp. 338-350
Author(s):  
Willian B. De Melo
Keyword(s):  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Production Capacity ◽  
Open Pit ◽  
Open Pit Mines ◽  
The Road ◽  
Advantages And Disadvantages ◽  
Mutation Operators ◽  
Ore Grades ◽  
On The Road

The allocation of trucks in open pit mines is a field with great potential for optimizing resources and applying advanced computer modeling techniques, mainly because many companies still choose to use manual allocation, which is premised on the decisions made by the operator, being subject to common failures and not reaching the maximum potential that the equipment can provide. Therefore, this work focuses on optimizing the allocation of trucks in order to increase production, reducing queue time and keeping ore grades within proper limits. The proposed algorithm was based on the differential evolution technique, where two types of mutation operators were used: rand/1/bin and best/1/bin, thus verifying the most suitable to solve the problem. The trucks were allocated in the ore loading and unloading process, aiming to improve the production capacity in a virtual mine. The results brought a convergence to the maximum global production, in addition to which, the allocation of unnecessary transport equipment to the planned routes was avoided. The two mutation operators compared had certain advantages and disadvantages, each better adapting to certain types of situations. The proposed technique can still be extended to other areas, for example, in the transport of grain on the road network or in the implementation of an allocation in freight cars that transport grain.

scholarly journals A Differential Evolution with Two Mutation Strategies and a Selection Based on an Improved Constraint-Handling Technique for Bilevel Programming Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Hong Li ◽  
Li Zhang
Keyword(s):  
Differential Evolution ◽  
Bilevel Programming ◽  
Differential Evolution Algorithm ◽  
Constraint Handling ◽  
Mutation Operators ◽  
Bilevel Programming Problems ◽  
Evolution Algorithm ◽  
Handling Technique ◽  
Mutation Strategies ◽  
Selection Operator

Two mutation operators are used in the differential evolution algorithm to improve the diversity of population. An improved constraint-handling technique based on a comparison mechanism is presented, and then it is combined with the selection operator in the differential evolution algorithm to fulfill constraint handling and selection simultaneously. A differential evolution with two mutation strategies and a selection based on this improved constraint-handling technique is developed to solve bilevel programming problems. The simulation results on some linear and nonlinear bilevel programming problems show the effectiveness and efficiency of the proposed algorithm.

scholarly journals Adaptive Differential Evolution Based on Simulated Annealing for Large-Scale Dynamic Economic Dispatch with Valve-Point Effects

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Dakuo He ◽  
Le Yang ◽  
Zhengsong Wang
Keyword(s):  
Simulated Annealing ◽  
Differential Evolution ◽  
Large Scale ◽  
Simulated Annealing Algorithm ◽  
Transmission Loss ◽  
Economic Dispatch ◽  
Evolutionary Process ◽  
Mutation Operators ◽  
Adaptive Differential Evolution ◽  
Dynamic Economic Dispatch

Dynamic economic dispatch (DED) that considers valve-point effects is a complex nonconvex and nonsmooth optimization problem in power systems. Over the past few decades, multiple approaches have been developed to solve this problem. In this paper, an adaptive differential evolution based on simulated annealing algorithm is proposed to solve the DED problem with valve-point effects. Simulated annealing (SA) algorithm is employed to carry out an adaptive selection mechanism in which the mutation operators of differential evolution (DE) are selected adaptively based on their historical performance. A mutation operator pool consisting of five operators is built to make each operator show its strength at different stages of the evolutionary process. Moreover, a heuristic strategy is introduced to transform infeasible solutions towards feasible ones to enhance the convergence rate of the proposed algorithm. The effectiveness of the proposed methods is demonstrated first on 10 popular benchmark functions with 100 dimensions, in comparison with the classic DE and five variants. Then, it is used to solve four DED problems with 10, 15, 30, and 54 units, which consider the valve-point effects, transmission loss, and prohibited operating zones. The simulation results are compared with those of state-of-the-art algorithms to clarify the significance of the proposed method and verify its performance. Three systems with 100-500 generators are also tested to confirm the advantages of the proposed method on large-scale DED problem.

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