Differential evolution using cooperative ranking-based mutation operators for constrained optimization

Xu, Bin; Zhang, Haifeng; Zhang, Meihua; Liu, Lilan

doi:10.1016/j.swevo.2019.06.007

Cited by 23 publications

(8 citation statements)

References 42 publications

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“…And then the combined level can be calculated using a calculation model [33]. Many models are available, and the simplest linear model is described by:…”

Section: Two-level Epsilon-constrained Methodsmentioning

confidence: 99%

“…Many researchers have pointed out that the search algorithm and constraint handling technique (CHT) are highly important for solving COPs [9]- [11], [33], [42]. Thus, improvement in the search ability and development of effective CHTs are commonly considered when solving COPs.…”

Section: Proposed Cetde a Basic Idea Of Cetdementioning

confidence: 99%

“…As mentioned above, DE was originally proposed for unconstrained problems. To enhance the search ability of DE when solving complex COPs, various kinds of approaches were proposed, such as the design of new mutation operator [10], [31]- [33], study of advanced parameter control strategies [10], [22], [34], [35], and introduction of additional diversity schemes [11], [21], [36].…”

Section: Introductionmentioning

confidence: 99%

“…Inspired by this framework, Wang et al proposed a constrained composite DE variant to solve COPs [38]. Xu et al proposed a cooperative rankingbased mutation strategy in DE for COPs [33]. Although the commonly used DE/rand/1 mutation strategy is adopted, it uses two different selection technique to determine parent vectors at two different situations.…”

Section: Introductionmentioning

confidence: 99%

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Constrained Optimization Based on Ensemble Differential Evolution and Two-Level-Based Epsilon Method

Zhang

2020

IEEE Access

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Constrained optimization problems (COPs) are common in many fields, and the search algorithm and constraint handling technique play important roles in the constrained evolution algorithms. In this paper, we propose a new optimization algorithm named CETDE based on ensemble differential evolution (DE) and a two-level epsilon-constrained method. In the ensemble DE variant, some promising parameters and mutation strategies constitute the candidate pool, and each element in the pool coexists throughout the search process and competes to generate new solutions. The two-level epsilon method is proposed by incorporating a generation and a population comparison level to retain more promising solutions without degrading the solution quality. Moreover, a diversity promotion scheme is developed to improve the population distribution when the search becomes trapped in a small region. The superior performance of CETDE is validated by comparison with some state-of-the-art COEAs over two sets of artificial benchmarks and five real-world problems. The competitive results show that CETDE is an effective method for solving COPs.

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“…And then the combined level can be calculated using a calculation model [33]. Many models are available, and the simplest linear model is described by:…”

Section: Two-level Epsilon-constrained Methodsmentioning

confidence: 99%

Section: Proposed Cetde a Basic Idea Of Cetdementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Constrained Optimization Based on Ensemble Differential Evolution and Two-Level-Based Epsilon Method

Zhang

2020

IEEE Access

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“…However, it is difficult to define the penalty function properly and, therefore, these methods are highly sensitive to the choice of the penalty function [43,164]. On the other hand, optimal solutions of most engineering problems lie on the constraint boundary [172,209], which means that an invalid solution near the constraint boundary may be converted to a high-quality valid solution with a repair technique. For instance, random repair operators have been proposed in [163].…”

Section: Ec For Semi-automated Multi-objective Wscmentioning

confidence: 99%

Distributed Data-intensive Web Service Composition

Sadeghiram¹

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<p>Service-oriented architecture (SOA) encourages the creation of modular applications involving Web services as the reusable components. Data-intensive Web services have emerged to manipulate and deal with the massive data emerged from technological advances and their various applications. Distributed Data-intensive Web Service Composition (DWSC) is a core of SOA, which includes the selection of data-intensive Web services from diverse locations on the network and composes them to accomplish a complicated task. As a fundamental challenge for service developers, service compositions must fulfil functional requirements and optimise Quality of Service (QoS), simultaneously. The QoS of a distributed DWSC is not only impacted by the QoS of component services and how the compositions are generated, but also by the locations of services and data transformation between services. However, existing works often neglect the impact of locations and data on service composition. The distributed DWSC has not been sufficiently studied in the literature. In this thesis, we first define the single-objective distributed DWSC that includes communication (e.g. bandwidth), Web service (execution time) and data (data cost) attributes. To this aim, we consider bandwidth information of communication links obtained using the location information of services. Based on the problem formulation, we then address the distributed DWSC problem by developing EC-based approaches. Those EC-based approaches are designed to incorporate domain-knowledge for effectively solving the distributed DWSC problem. Afterwards, we study the multi-objective distributed DWSC to satisfy different QoS requirements. In particular, the QoS-constrained distributed DWSC problem and user preferences are considered. For finding trade-off solutions for those problems, new Multi-objective Evolutionary Algorithms (MOEAs) are proposed based on the current Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Furthermore, a new problem formulation for the dynamic distributed DWSC (D2−DWSC) problem with bandwidth fluctuations is proposed. An EC-based approach is developed to solve the D2-DWSC. Finally, extensive empirical evaluations are conducted that demonstrate the high performance of our proposed methods in finding composite services with good QoS.</p>

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A Novel Repair-Based Multi-objective Algorithm for QoS-Constrained Distributed Data-Intensive Web Service Composition

Sadeghiram

Chen

2020

Web Information Systems Engineering – WISE 2020

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Differential evolution using cooperative ranking-based mutation operators for constrained optimization

Cited by 23 publications

References 42 publications

Constrained Optimization Based on Ensemble Differential Evolution and Two-Level-Based Epsilon Method

Constrained Optimization Based on Ensemble Differential Evolution and Two-Level-Based Epsilon Method

Distributed Data-intensive Web Service Composition

A Novel Repair-Based Multi-objective Algorithm for QoS-Constrained Distributed Data-Intensive Web Service Composition

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