Quantum Inspired Social Evolution (QSE) algorithm for 0-1 knapsack problem

Pavithr, R. S.; Gursaran,

doi:10.1016/j.swevo.2016.02.006

Cited by 36 publications

(11 citation statements)

References 35 publications

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“…In [54], a mechanism to incorporate human bias in the selection of individuals through a second opinion when interactions between individuals are indecisive was proposed. Algorithm 15 shows the pseudocode of the quantum-inspired social evolution algorithm (QSE) [52]. The decision-making process is biased by subjective or objective knowledge.…”

Section: Social Evolution Algorithmmentioning

confidence: 99%

A Review of Quantum-Inspired Metaheuristics: Going From Classical Computers to Real Quantum Computers

Montiel

2020

IEEE Access

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This paper presents a review of quantum-inspired population-based metaheuristics. Quantuminspired algorithms were born when there were no quantum computers; they demonstrated to have interesting characteristics providing good results in classical computers. At present, when the first quantum computers are available, scientists are working to confirm the quantum supremacy in different fields. After almost 20 years that the first metaheuristic inspired in quantum phenomena was published, a large number of works have been proposed. This paper aims to look back to see which quantum-inspired metaheuristics could be translated to be used in the existing quantum computers based on the circuit model programming paradigm. Reviewed metaheuristics were classified according to their main source of inspiration; just some representative works of each classification were selected because of the vast number of existing works on each one. The analysis was done for the circuit model and metrics as width, size, and length were used to determine their viability of being implemented in a real quantum computer. Moreover, comparative results using metrics such as performance and running time for quantum-inspired metaheuristic were included. INDEX TERMS Quantum metaheuristic, quantum-inspired, circuit model, metaheuristic for quantum computer, binary coded quantum-inspired metaheuristic, real coded quantum-inspired metaheuristic.

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Section: Social Evolution Algorithmmentioning

confidence: 99%

A Review of Quantum-Inspired Metaheuristics: Going From Classical Computers to Real Quantum Computers

Montiel

2020

IEEE Access

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“…The proposed QSE algorithm was applied to the 0-1 knapsack problem and the performance of the algorithm was compared to various evolutionary, swarm, and quantum-inspired evolutionary algorithmic variants. Pavithr and Gursaran claim that the performance of the QSE algorithm is better than or at least comparable to the different evolutionary algorithmic variants it was tested against [8].…”

Section: Related Workmentioning

confidence: 99%

Combinatorial GVNS (General Variable Neighborhood Search) Optimization for Dynamic Garbage Collection

et al. 2018

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General variable neighborhood search (GVNS) is a well known and widely used metaheuristic for efficiently solving many NP-hard combinatorial optimization problems. We propose a novel extension of the conventional GVNS. Our approach incorporates ideas and techniques from the field of quantum computation during the shaking phase. The travelling salesman problem (TSP) is a well known NP-hard problem which has broadly been used for modelling many real life routing cases. As a consequence, TSP can be used as a basis for modelling and finding routes via the Global Positioning System (GPS). In this paper, we examine the potential use of this method for the GPS system of garbage trucks. Specifically, we provide a thorough presentation of our method accompanied with extensive computational results. The experimental data accumulated on a plethora of TSP instances, which are shown in a series of figures and tables, allow us to conclude that the novel GVNS algorithm can provide an efficient solution for this type of geographical problem.

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“…Pavithr et al claim that the performance of the QSE algorithm is better than or at least comparable to the different evolutionary algorithmic variants it was tested against [8]. The search progresses from one generation to the next, while the quantum bits evolve gradually to increase the probability of region selection [11].…”

Section: Related Workmentioning

confidence: 99%

Quantum Inspired General Variable Neighborhood Search (qGVNS) for Dynamic Garbage Collection

Papalitsas¹,

Karakostas²,

Andronikos³

et al. 2017

Preprint

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General Variable Neighborhood Search (GVNS) is a well known and widely used metaheuristic for efficiently solving many NP-hard combinatorial optimization problems. Quantum General Variable Neighborhood Search (qGVNS) is a novel, quantum inspired extension of the conventional GVNS. Its quantum nature derives from the fact that it takes advantage and incorporates tools and techniques from the field of quantum computation. Travelling Salesman Problem (TSP) is a well known NP-Hard problem which has broadly been used for modelling many real life routing cases. As a consequence, TSP can be used as a basis for modelling and finding routes for Geographical Systems (GPS). In this paper, we examine the potential use of this method for the GPS system of garbage trucks. Specifically, we provide a thorough presentation of our method accompanied with extensive computational results. The experimental data accumulated on a plethora of symmetric TSP instances (symmetric in order to faithfully simulate GPS problems), which are shown in a series of figures and tables, allow us to conclude that the novel qGVNS algorithm can provide an efficient solution for this type of geographical problems.

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Quantum Inspired Social Evolution (QSE) algorithm for 0-1 knapsack problem

Cited by 36 publications

References 35 publications

A Review of Quantum-Inspired Metaheuristics: Going From Classical Computers to Real Quantum Computers

A Review of Quantum-Inspired Metaheuristics: Going From Classical Computers to Real Quantum Computers

Combinatorial GVNS (General Variable Neighborhood Search) Optimization for Dynamic Garbage Collection

Quantum Inspired General Variable Neighborhood Search (qGVNS) for Dynamic Garbage Collection

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