Quantum inspired genetic programming. This paper provides a unified framework and a .

 
Quantum inspired genetic programming May 8, 2024 · QGA, a genetic algorithm embedded with quantum mechanics, combines the advantages of quantum computing and genetic algorithms, enabling faster and more robust convergence to the optimum. Genetic programming is utilized to give a linear equation for calculating the degree of toxicity more accurately. The suggested scheme relies on the concept of superposition fitness selection to enhance the traditional GP selection strategy, to reduce the computational cost, and Oct 18, 2014 · We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP), which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model for symbolic regression. This paper is the first to propose a quantum-inspired genetic algorithm (QGA) for permutation flow shop scheduling problem to minimize the maximum completion time (makespan). In this case, genetic programming is used in the induction of Nov 14, 2024 · Researchers developed a quantum-inspired genetic algorithm that merges natural selection principles with quantum mechanics to optimize photonic layer designs, specifically for transparent radiative cooling systems. The reliable prediction of toxic effects of chemicals in living systems is highly desirable in domains such as cosmetics, drug design, food safety, and the JIAO et al. QIMuLGP allows us to explore a different genotypic representation (i. Sep 1, 2013 · In this work we present the application of quantum inspired linear genetic programming (QILGP) to the growth of self-assembled quantum dots. Parse tree for the S-expression (+ a (/ (-(3 a)) 5)). In (Lee, Lin, Liao, & Tsao, 2011) a QGA is proposed in order to solve the problem of the economic dispatch that includes wind power generation. Given the computational difficulties of determining optimal feature subsets, heuristic and metaheuristic algorithms have been widely used. ). The first quantum-inspired genetic algorithm was introduced by Kim and Han []. Quantum Inspired Genetic algorithm for feature subset selection with distributed simulated quantum annealing using Python and Julia. They help in efficiently exploring the solution space, leading to faster convergence and better optimization results. Aug 13, 2020 · Abstract. Jul 6, 2018 · Toward a Quantum-Inspired Linear Genetic Programming Model. - speQtrum/QGA_QSA Jun 24, 2019 · Genetic algorithms, which mimic evolutionary processes to solve optimization problems, can be enhanced by using powerful semi-local search algorithms as mutation operators. 1 Quantum-inspired genetic algorithms (QGAs). Lu. Jan 1, 2007 · Next, it describes an application of genetic programming for evolving quantum computing circuits. Therefore, it is necessary to understand the technical evolution of quantum inspired solvers to break the bottleneck. Langdon from gp-bibliography. This repository contains some unpublished before source codes developed by Robert Nowotniak in the years 2010-2015. Oct 17, 2023 · The quantum-inspired genetic algorithm (QGA), which combines quantum mechanics concepts and GA to enhance search capability, has been popular and provides an efficient search mechanism. 1, June 2019 Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. This thesis proposes, develops and tests a novel model of quantum-inspired evolutionary algorithm named Quantum-Inspired Linear Genetic Programming (QILGP) for the evolution of machine code programs. Since the first QIGA was proposed, it has been applied to a large number of optimization problems. computation. For solving high-dependency optimization problems, QE-DE integrates entangled states in its Qubits (or quantum bit). In this paper we provide a brief background of quantum computers. Lee Spector (1998, 2004) explored the use of genetic programming to evolve new quantum Dec 1, 2002 · The results show that QEA performs well, even with a small population, without premature convergence as compared to the conventional genetic algorithm, and a Q-gate is introduced as a variation operator to drive the individuals toward better solutions. In this case, genetic programming is used in the induction of Jul 12, 2011 · This paper proposes a novel QIEA (Quantum-Inspired Linear Genetic Programming - QILGP) for automatic synthesis of machine code (MC) programs and aims to present a preliminary evaluation of In a Quantum Inspired Genetic Programming “QIGP” model for toxicity prediction is proposed. The second serious undertaking combining quantum and evolutionary computation was perhaps inspired by the use of genetic programming to obtain novel circuit designs (Koza, 1997). Fitness superposition is used to enhance the selection method and to We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP), which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model for symbolic regression. This paper describes the latest version of a QIEA model (“Quantum-Inspired Linear Genetic Programming” - QILGP) to evolve machine code programs. Jan 1, 2003 · This paper proposes a novel evolutionary algorithm inspired by quantum computing, called a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and principles of quantum May 20, 1996 · It is informally shown that the quantum inspired genetic algorithm performs better than the classical counterpart for a small domain. Google Scholar Z. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum in quantum computation. Free of human preconceptions or biases, the adaptive nature of EAs can generate solutions that Jul 7, 2001 · These quantum algorithms rely upon the inherent parallel qualities of quantum computers to achieve their improvement. In International Conference on Evolutionary Computation, pages 61-66, 1996. In this study, we incorporate a series of dual-variable approximation techniques into the paradigm of a quantum-inspired genetic algorithm (QIGA) and devise an efficient evaluation function based on these techniques. quantum-inspired evolutionary algorithm May 18, 2009 · This paper proposes a novel QIEA (Quantum-Inspired Linear Genetic Programming - QILGP) for automatic synthesis of machine code (MC) programs and aims to present a preliminary evaluation of applying the quantum-inspiration paradigm to evolve programs by using two symbolic regression problems. The former adopts This research proposes a novel approach called Quantum-Inspired Fuzzy Genetic Programming (QIFGP) that integrates concepts from Article Info Rule generation in complex data analysis tasks poses challenges in terms of accuracy and interpretability. Most of the modern works that use the term quantum-inspired evolutionary algo-rithm or quantum genetic algorithm (QGA) use the work of Han and Kim [40], [36] as a reference. The quantum genetic algorithm is primarily centered on the principles of subatomic particles and the state of the considerable superposition. [12]. linear), and to use more than one genotype per individual, combining their Cheminformatics plays a vital role in maintaining large amounts of chemical data. Apr 1, 2022 · Quantum Genetic Algorithm (QGA) (Narayanan & Moore, 1996) is a quantum-inspired evolutionary algorithm proposed in 1996, in order to solve the traveling salesperson problem. 2023. Jan 3, 2022 · Genetic algorithms (GA) are computational methods for solving optimization problems inspired by natural selection. His-current research interest includes Machine learning, Nature inspired computing, Quantum inspired computing, Multi-criteria optimization and Meta-heuristics based techniques. QuaLiGP is inspired on multi-level quantum systems, and its operation is based on quantum individuals, which represent a superposition of all programs (solutions Quantum Inspired Genetic Programming Model to Predict Toxicity Degree for Chemical Compounds Cheminformatics plays a vital role to maintain a large amount of chemical data. In the QGA, Q-bit based representation is employed for exploration in discrete 0-1 hyperspace by using updating operator of quantum gate as well as genetic operators of Q-bit. Recently, the rise of quantum computing has led to the exploration of quantum-inspired Aug 1, 2024 · We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP), which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model for symbolic regression. EAs are used to discover solutions to problems humans do not know how to solve, directly. May 1, 2009 · Quantum Inspired Linear Genetic Programming (QILGP), whose preliminary version is presented in [9], evolves x86 machine code programs. The so called Quan- tum Evolutionary Programming has two major sub-areas: Quantum Inspired Genetic Algorithms (QIGAs) and Quantum Genetic Algorithms (QGAs). Created by W. We study the practical performance of quantum-inspired algorithms for recommendation systems and linear systems of equations. The optimization process is further accelerated by utilizing the quantum local search. The basic terminology of quantum mechanics is introduced before a comparison is made between a classical genetic algorithm and a quantum inspired method for the travelling We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP), which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model for symbolic regression. 2022), qauntum-inspired cultural algorithm (Guo et al. Digital Library. We present a simple quantum approach to genetic algorithms and analyze its benefits and drawbacks. Qubit is a dual quanta Sep 22, 2023 · The quantum-inspired parallel annealing method implemented in memristor-based hardware has demonstrated significant improvements in time- and energy-efficiency compared to previously reported May 25, 2016 · Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. The basic terminology of quantum mechanics Apr 1, 2022 · A review of quantum-inspired meta-heuristic algorithms is given in (Montiel Ross, 2020). Evolutionary Computation Conference 1 (2009), 1691--1698. The optimal solution of COMPUTATIONAL PHYSICS QUANTUM CIRCUIT DESIGN BY MEANS OF GENETIC PROGRAMMING ANDREI BÃUTU1, ELENA BÃUTU2 1 “Mircea cel Bătrân” Naval Academy, Constantza, 900218, Romania, abautu@anmb. Because we can simulate the quantum circuits that implement GA in different highly configurable noise models and even run GA on actual quantum Dec 12, 2014 · We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP), which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model for symbolic regression. Saad Mohamed Darwish (Quantum Inspired Genetic Programming Model to Predict Toxicity Degree for Chemical Compounds) An insight into the potential benefits of using optimization-based prediction models for toxicity real valued-data is provided in [25]. The potential Conventional quantum-inspired exploration procedures employ the idea of superposition state to deal with combinatorial difficulties Saad Mohamed Darwish (Quantum Inspired Genetic Programming Model to Predict Toxicity Degree for Chemical Compounds) ISSN: 2579-7298 International Journal Of Artificial Intelegence Research Vol. MATH Google Scholar A. This is the final parallel processing of these experiments (Kuo, S. In our case, we used the term QGA to reference the work of Han and Kim, with Oct 24, 2008 · A novel evolutionary computing method-quantum inspired genetic algorithms-is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more efficient Sep 5, 2022 · A Hybrid Quantum Genetic Algorithm with an Adaptive Rotation Angle (HQGAAA) for the 0-1 knapsack problem is presented. . 3, No. H. Reference [4] combined evolutionary theory and quantum theory to propose a new kind of evolutionary programming, the Quantum Evolutionary Dec 1, 2024 · Quantum-Inspired Operators: Quantum Crossover and Mutation: These operators are utilized in the QGAO to enhance the exploration capabilities of the genetic algorithm. In [ 8 , 9 ], the possibilities of using genetic programming to create new quantum algorithms were explored. Genetic Programming is utilized to give a linear equation for calculating toxicity degree more accurately. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i. The Resource-Constrained Project-Scheduling Problem (RCPSP) is an NP-hard problem which can be found in many research domains. Sep 24, 2024 · The second major effort, combining quantum and evolutionary computing, was inspired by the prospect of using genetic programming to synthesize new quantum circuits and algorithms . g. Narayanan and M. Also, there has been some works in the designing of genetic algorithms based on quantum theoretical concepts and techniques. A Multi-Objective Decomposition Optimization Method for Refinery Crude Oil Scheduling through Genetic Programming. These adaptations allow classical systems to perform tasks such as image recognition, natural language processing, and financial forecasting more May 3, 2019 · This paper proposes a quantum‐inspired genetic programming model to improve prediction accuracy. Genetic programming is such a nature inspired meta-heuristic that has been applied to various artificial intelligence problems with great success. : QUANTUM-INSPIRED IMMUNE CLONAL ALGORITHM FOR GLOBAL OPTIMIZATION 1235 genetic programming [18]–[20]. Jan 30, 2024 · 1 QiGA Quantum-inspired genetic programming algorithm (Pereira et al. We present in this paper a novel genetic Jan 1, 2011 · Quantum inspired linear genetic programming is a novel model to evolve machine code programs exploiting quantum mechanics principles. Quantum-inspired genetic algorithm (QGA), which were firstly developed by Narayanan [3], is a novel algorithm. ‪Professor, Auckland University of Technology‬ - ‪‪Cited by 4,380‬‬ - ‪Artificial intelligence‬ - ‪bioinformatics‬ - ‪computational statistics‬ - ‪machine learning‬ Saad Mohamed Darwish (Quantum Inspired Genetic Programming Model to Predict Toxicity Degree for Chemical Compounds) An insight into the potential benefits of using optimization-based prediction models for toxicity real valued-data is provided in [25]. Jun 29, 2010 · Quantum-inspired evolutionary algorithms, one of the three main research areas related to the complex interaction between quantum computing and evolutionary algorithms, are receiving renewed attention. The so called Quantum Evolutionary Programming has two major sub-areas: Quantum Inspired Genetic Algorithms (QIGAs) and Quantum Genetic Algorithms (QGAs). Jun 6, 2018 · This paper proposes a Quantum Inspired Genetic Programming “QIGP” model to improve the prediction accuracy. Mar 12, 2020 · This paper proposes a novel QIEA (Quantum-Inspired Linear Genetic Programming - QILGP) for automatic synthesis of machine code (MC) programs and aims to present a preliminary evaluation of Aug 21, 2019 · The general programming implementation characteristics of the GA, ACO, PSO, QGA, and AQGA are described in the next paragraphs. The This paper proposes a novel QIEA (Quantum-Inspired Linear Genetic Programming -QILGP) for automatic synthesis of machine code (MC) programs and aims to present a preliminary evaluation of applying the quantum-inspiration paradigm to evolve programs by using two symbolic regression problems. May 18, 2009 · A new approach for the Quantum-Inspired Grammar-based Linear Genetic Programming (QIGLGP) evolutionary algorithm to handle the multiple objectives of the problem using the non-dominance concept is proposed, and the Pareto front of these accepted runs contains a set of non-dominated solutions that could be analyzed by the decision maker for his a posteriori decision. A quantum-inspired evolutionary algorithm is a new evolutionary algorithm for a classical computer rather than for quantum mechanical hardware. e. ‪Professor, Auckland University of Technology‬ - ‪‪Cited by 4,372‬‬ - ‪Artificial intelligence‬ - ‪bioinformatics‬ - ‪computational statistics‬ - ‪machine learning‬ constrain quantum-inspired computing to methods for solv-ing engineering problems with cyclic or recurrent behavior. In Proceedings of IEEE Quantum-inspired genetic algorithms (QGAs) The first quantum-inspired genetic algorithm was introduced by Kim and Han . linear), and to use more than one genotype per individual, combining their outputs using least squares method (multi-gene approach Quantum-inspired evolutionary algorithms (QIEAs) exploit principles of quantum mechanics to improve the performance of classical evolutionary algorithms. logD7 dataset, which contains phenol descriptors, and angle encoding were adopted. In 2000, Han and Kim [1] proposed a genetic quantum algorithm to solve knapsack problems and gave the definition and operation method of QRG, in which directions and magnitudes of the rotation angle, the only operation parameter, are given by a lookup table. superposition of states) to perform computations. Linear Genetic Programming is so named because each of its individuals is represented by a list of instructions (linear structures), which are A meta-heuristic quantum inspired genetic programming with a dynamic model is proposed where the remote archive of non-dominated and optimal solutions and the best population achieved by a dynamic genetic quantum algorithm with quantum rotation gate with their Genetic programming is such a nature inspired meta-heuristic that has been applied to various artificial intelligence problems with great success. Genetic algorithms + data structures = evolution, programs (2nd, extended ed. M. Quantum dots are nanostructures that have been widely applied Apr 10, 2022 · Quantum-inspired Ising machines, as a new computing paradigm, can be used to solve integer programming problems by reducing them into Ising models. Quantum inspired genetic algorithms. The former adopts qubit chromosomes as representations and employs quantum gates for the search of the best solution. This novel proposal uses the Deutsch-Jozsa quantum circuit to generate quantum populations, which synergistically works as haploid recombination and mutation operators taking advantage of quantum entanglement providing exploitative and explorative features to produce new Jun 1, 2012 · We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP), which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model for symbolic regression. In (Han & Kim, 2002) a quantum-inspired evolutionary algorithm is proposed for solving the knapsack problem. Genetic Programming is utilized to give a linear equation for calculating toxicity Mar 4, 2004 · Recently, researchers have applied genetic algorithms (GAs) to address some problems in quantum computation. Quantum Genetic Algorithm Quantum genetics algorithms arise in the field of quantum processing. The fusion of quantum mechanics with optimization methods can potentially address NP-hard problems more efficiently and exponentially faster. A quantum-inspired genetic algorithm is a variation and improvement of a classical genetic algorithm that utilizes qubit chromosome representation instead of conventional models, namely binary, numerical, and symbolic. This has motivated the creation of quantum-inspired Jan 30, 2024 · Quantum algorithms, based on the principles of quantum mechanics, offer significant parallel processing capabilities with a wide range of applications. The so called Quan-tum Evolutionary Programming has two major sub-areas: Quantum Inspired Genetic Algorithms (QIGAs) and Quantum Genetic Algorithms (QGAs). Springer, Berlin Heidelberg New York 1994. A quantum-inspired genetic algorithm is a variation and improvement of a classical genetic algorithm that utilizes qubit chromosome representation instead of conventional models, namely binary, numerical, and symbolic. Moore. Recently, authors in [5], [6] have provided compelling evidence to support the notion that QCs can currently offer valuable capabilities, even with their inherent noise at the moment, and prior to the advent of fault-tolerant systems. QIGAs and HGAs are algorithms that mix classical computation with quantum operators, using qubits for chromosome representations and quantum gates for operators. Add this topic to your repo To associate your repository with the quantum-inspired-genetic-algorithm topic, visit your repo's landing page and select "manage topics. Also, there has been some works in the designing of genetic algorithms based on quantum Jun 20, 1996 · A novel evolutionary computing method-quantum inspired genetic algorithms-is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more efficient Jul 24, 2023 · Quantum Entanglement inspired Differential Evolution algorithm (QE-DE) has been proposed in this paper to solve the drawbacks of DE. Jul 6, 2018 · We propose a new approach for the Quantum-Inspired Grammar-based Linear Genetic Programming (QIGLGP) evolutionary algorithm to handle the multiple objectives of the problem using the non-dominance Owing to the problem complexity, a majority of the research efforts have focused on tackling this problem using meta-heuristics. Information is stored as qubits in quantum computers. The other concentrates on quantum-inspired evolutionary computing for a Oct 15, 2019 · The key purpose of this paper is to investigate the accuracy of an adapted Quantum-Inspired Genetic programming (QIGP) for the estimation of toxicity degree of chemical compounds. It is targeted at the investigation of how Quantum-inspired Genetic Algorithm (QGAGA) modulates (QIGA). and population dynamical processes such as reproduction, selection, etc. This paper proposes a novel evolutionary algorithm inspired by quantum computing, called a quantum-inspired evolutionary algorithm (QEA), which Aug 23, 2012 · Aiming to exploit this new paradigm on genetic programming (GP), this paper introduces a novel QIEA model (quantum-inspired linear GP—QuaLiGP), which evolves machine code programs. mutation, crossover, etc. The conventional genetic algorithm determines the fixed qubits’ positions (presented with gray background) and their binary values in the individuals’ register of the Reduced Quantum Genetic Algorithm, thus controlling the number of qubits in III. , Chou, Y. Quantum inspired linear genetic programming is a novel Aug 6, 2002 · A novel evolutionary computing method-quantum inspired genetic algorithms-is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more efficient evolutionary computing methods. Quantum-inspired evolutionary algorithms (QIEAs) exploit principles of quantum mechanics to improve the performance of classical evolutionary algorithms. Nature-inspired stochastic optimization algorithms have long been a research hotspot. This has motivated the creation of quantum-inspired evolutionary algorithms (QIEAs), which successfully use some quantum physics principles to improve the performance of evolutionary algorithms (EAs The huge performance superiority of quantum computers for some specific problems lies in their direct use of quantum mechanical phenomena (e. These algorithms were shown to have an exponential asymptotic speedup compared to previously known classical methods for problems involving low-rank matrices, but with complexity bounds that exhibit a hefty polynomial overhead compared to quantum algorithms. , 2017). In this paper, the concept and traditional algorithms for MILP are introduced. ro Received September 12, 2006 Research in quantum technology has shown that quantum computers can provide dramatic Jun 10, 2012 · The latest version of a QIEA model (“Quantum-Inspired Linear Genetic Programming” - QILGP) to evolve machine code programs outperforms AIMGP by obtaining better solutions with fewer parameters and operators. Aiming to exploit this new paradigm on genetic programming (GP), this paper introduces a novel QIEA model (quantum-inspired linear GP—QuaLiGP), which evolves machine code programs. QILGP is inspired on multilevel quantum systems and its operation is based on quantum Sep 27, 2024 · Techniques like quantum-inspired neural networks (QINNs) and quantum-inspired support vector machines (SVMs) use probabilistic methods and optimization techniques derived from quantum computing. Further, some studies emphasize the use of quantum bits or Q-bits as the defining aspect of being quantum-inspired [26], [27], while others characterize different quantum concepts to be the core underpinning of the “quantum It is apparent from the results that quantum mutation, quantum crossover and representation of quantum superposition using quantum gates enhances population diversity and the QIGA is also found to outperform many other evolutionary algorithms. 2020), quantum-inspired memetic algo-rithm (Zhang et al. We describe the quantum advantage of true randomness. The findings showed that the QIGP model is more efficient than the classical neural network model and it could be a substitute for costly and time-consuming Jul 12, 2014 · Aiming to exploit this new paradigm on genetic programming (GP), this paper introduces a novel QIEA model (quantum-inspired linear GP-QuaLiGP), which evolves machine code programs. We propose the Quantum-Inspired Multi-Gene Lin-ear Genetic Programming (QIMuLGP), which is a generalization of Quantum-Inspired Linear Genetic Programming (QILGP) model for symbolic regression. QGA is essentially a kind of genetic algorithm which can be applied when the conventional GA ( Goldberg, 1989 ) is unable. They were used for research on advanced randomised search algorithms (mainly quantum-inspired evolutionary and genetic algorithms and other population methods) for numerical and Jul 19, 2023 · Over the past few years, quantum-inspired genetic algorithm, as the forerunner of quantum evolutionary algorithms has made significant achievements in solving optimization problems in various fields. The ability of this algorithm to comprehensively search the problem space and discover global extrema is due to the power of the exploration process in this algorithm, which in turn is attributed Oct 23, 2022 · 2. QEA is a probabilistic set of rules exploiting quantum computation’s electricity to boost genetic tactics. and Chen, C. The suggested scheme relies on the concept of superposition fitness selection to enhance the traditional GP selection strategy, to reduce the computational cost, and Mar 4, 2004 · A survey of the main works in GAs plus quantum computing including also the application of GAs for learning quantum operators and circuit design and quantum evolutionary programming is considered. Apr 1, 2017 · A novel hybrid quantum inspired genetic algorithm (HQIGA) is proposed in this current work by embedding the concepts of quantum computing. A novel evolutionary computing method-quantum inspired genetic algorithms-is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more efficient evolutionary computing methods. This paper proposes a modified QGA, called dynamic QGA (DQGA). Using the design of planar multilayer photonic structures for transparent radiative cooling as a testbed, we show superiority of our algorithm over the Sep 1, 2020 · A new algorithm is proposed that integrates linear and grammar-guided genetic programming concepts with a quantum-inspired approach to create programs that represent a crude oil refinery scheduling solution and a success ratio is proposed to evaluate the algorithm performance. bib Revision:1. Using a quantum-inspired approach, QILGP shows best device of two QIEAs: the quantum genetic algorithm and the adaptive quantum genetic algorithm. Quantum-inspired genetic algorithms. , mutation, crossover, etc. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in domains such as cosmetics, drug design, food safety, and manufacturing chemical Sep 1, 2021 · The Quantum Inspired Meta-Heuristic (QIMH) Algorithm is a synergistic combination of evolutionary algorithm, quantum computing, meta-heuristic, and multi-objective approaches to solve hard, exhaustive problems, and to get the best optimization. We have just a few examples of fully Quantum Genetic Algorithms (QGA), which focus Sep 1, 2021 · The Quantum Inspired Meta-Heuristic (QIMH) Algorithm is a synergistic combination of evolutionary algorithm, quantum computing, meta-heuristic, and multi-objective approaches to solve hard, exhaustive problems, and to get the best optimization. The fitness function comprises four objectives that guide the evolution based on importance predefined by the decision maker. A superposition of states may be used to house quantum computers. However, HQIGA uses a qubit due to probabilistic representation and obviates binary representation. Jul 24, 2023 · We propose a new approach for the Quantum-Inspired Grammar-based Linear Genetic Programming (QIGLGP) evolutionary algorithm to handle the multiple objectives of the problem using the non-dominance Quantum-Inspired Genetic Programming Algorithm for the Crude Oil Scheduling of a Real-World Refinery . Aug 1, 2019 · Request PDF | Quantum‐inspired genetic programming model with application to predict toxicity degree for chemical compounds | Cheminformatics plays a vital role in maintaining large amounts of Oct 1, 2018 · Quantum rotation gate (QRG) is the most commonly used quantum gate in QEA. Apr 16, 2024 · Figure 2: The overview of applying genetic algorithm optimization to reduce the number of Grover iterations entailed by running the RQGA algorithm. Nov 13, 2024 · We propose a novel optimization strategy based on an active learning scheme that combines the Quantum-inspired Genetic Algorithm (QGA) with machine learning surrogate model regression. This article proposes a new algorithm that integrates linear and grammar-guided genetic programming concepts with a quantum-inspired approach to create programs that represent a crude oil refinery scheduling solution. This paper provides a unified framework and a evolutionarymulti-objectiveoptimization,decomposition,quantum-inspired algorithm, genetic programming, refinery scheduling ACM Reference Format: Cristiane Salgado Pereira, Douglas Mota Dias, Luis Martí, and Marley Vel-lasco. QIMuLGP allows us to explore a different genotypic About Genetic Programming Genetic Programming (GP) is a type of Evolutionary Algorithm (EA), a subset of machine learning. Refinery scheduling comprises a group of decisions that aims to optimize asset allocation, activity sequencing, and Sep 1, 2021 · In addition, quantum inspired genetic algorithm is a class of quantum inspired evolutionary algorithms used to elucidate combinatorial optimization [19], and metaheuristic algorithms are highly nonlinear, complex, and stochastic [20] and are improved by firefly algorithms [21]. This paper describes the Nov 17, 2024 · Feature subset selection is essential for identifying relevant and non-redundant features, which enhances classification accuracy and simplifies machine learning models. This paper proposes a Quantum Inspired Genetic Programming “QIGP” model to improve the prediction accuracy. Mar 11, 2024 · Quantum-inspired Ising machines, as a new computing paradigm, can be used to solve integer programming problems by reducing them into Ising models. Y. Here, we introduce reverse quantum annealing, a class of quantum evolutions that can be used for performing families of quasi-local or quasi-nonlocal search starting from a classical state, as novel sources of mutations The Quantum-stimulated techniques can be classified into three predominant groups: the evolutionary-designed quantum algorithms (EDQAs), Quantum EAs (QEAs), and the quantum-inspired EAs (QIEAs). Quantum Inspired Genetic Programming Model to Predict Toxicity Degree for Chemical Compounds Cheminformatics plays a vital role to maintain a large amount of chemical data. linear), and to use more than one genotype per individual, combining their Oct 1, 2024 · Quantum computing is a promising direction to deliver a solution to the high computational complexity of MILPs. QGA achieves much better performance than classical genetic algorithm. Tu and Y. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in domains such as cosmetics, drug design, food safety, and manufacturing chemical on merging evolutionary computation and quantum computing has being carried out since the late 1990s and can be classified into two fields; 1) new quantum algorithms using automatic programming techniques such as genetic programming [21], 2) quantum-inspired evolutionary computing for a digital Some authors tackled the problem of quantum circuit design with nature-inspired algorithms. The huge performance superiority of quantum computers for some specific problems lies in their direct use of quantum mechanical phenomena (e. ro 2 “Ovidius” University, Constantza, 900527, Romania, erogojina@univ-ovidius. Recently, researchers have applied genetic algorithms (GAs) to address some problems in quantum computation. Quantum-inspired evolutionary algorithms could be considered part of this branch. " Jun 1, 2021 · Due to this limitations, a new version of evolutionary algorithms called quantum-inspired genetic algorithm was proposed that is based on the principles of quantum computing and genetic algorithm. 1. 1 Biologically-inspired metaheuristics 2. Google Scholar [10] Download scientific diagram | The quantum‐inspired genetic programming prediction model from publication: Quantum‐inspired genetic programming model with application to predict toxicity degree consists of Quantum-Inspired Genetic Algorithms (QIGA) or Hybrid Genetic Algorithms (HGA). Quantum computing is empl Feb 1, 2024 · He has published several papers in the area of meta-heuristics, multi-criteria optimization and nature inspired computing. the term Quantum Evolutionary Programming (QEP)9, which comprises two significant directions, namely Quantum-Inspired 25 26 Genetic Algorithms–QIGAs (or Hybrid Genetic Algorithms–HGAs) and Oct 15, 2019 · The key purpose of this paper is to investigate the accuracy of an adapted Quantum-Inspired Genetic programming (QIGP) for the estimation of toxicity degree of chemical compounds.