Memetic Approach Research Articles

Finding Near-Optimal Weight Independent Sets at Scale

Computing maximum weight independent sets in graphs is an important NP-hard optimization problem. The problem is particularly difficult to solve in large graphs for which data reduction techniques do not work well. To be more precise, state-of-the-art branch-and-reduce algorithms can solve many large-scale graphs if reductions are applicable. Otherwise, their performance quickly degrades due to branching requiring exponential time. In this paper, we develop an advanced memetic algorithm to tackle the problem, which incorporates recent data reduction techniques to compute near-optimal weight independent sets in huge sparse networks. More precisely, we use a memetic approach to recursively choose vertices that are likely to be in a large-weight independent set. We include these vertices into the solution, and further reduce the graph. We show that identifying and removing vertices likely to be in large-weight independent sets opens up the reduction space and speeds up the computation of large-weight independent sets remarkably. Our experimental evaluation indicates that we are able to outperform state-of-the-art algorithms. For example, our two algorithm configurations compute the best results among all competing algorithms for all instances tested. Thus, it can be seen as a useful tool when large-weight independent sets need to be computed in practice.

Enhancing English Writing Skills Through Internet-Plus Tools in the Perspective of Memetics

This investigation delves into incorporating a hybridized memetic strategy within the framework of English composition pedagogy, leveraging Internet Plus resources. The study aims to provide an in-depth analysis of how this method influences students’ writing competence, their perceptions of writing, and their enthusiasm for English acquisition. Employing an explanatory research design that combines qualitative and quantitative methods, the study collects data through surveys, interviews, and observations of students’ writing performance before and after the intervention. Findings demonstrate a beneficial impact of integrating the memetic approach alongside Internet Plus tools on the writing aptitude of English as a Foreign Language (EFL) learners. Students reported increased engagement with writing, attributing it to the use of Internet plus tools. They also expressed that the memetic approach facilitated a deeper understanding of cultural and social contexts in writing. Furthermore, the findings highlight a significant improvement in students’ writing skills following the intervention. This study provides significant insights into the practical implementation of the memetic approach within English writing education, highlighting the beneficial contribution of Internet Plus tools in enriching students' learning journeys.

Reinforming memes: a literature review of the status of memetic information

PurposeOur purpose is to reconnect memetics to information, a persistent and unclear association. Information can contribute across a span of memetic research. Its obscurity restricts conversations about “information flow,” the connections between “form” and “content,” as well as many other topics. As information is involved in cultural activity, its clarification could focus memetic theories and applications.Design/methodology/approachOur design captures theoretical nuance in memetics by considering a long standing conceptual issue in memetics: information. A systematic review of memetics is provided by making use of the term information across literature. We additionally provide a citation analysis and close readings of what “information” means within the corpus.FindingsOur initial corpus is narrowed to 128 pivotal memetic publications. From these publications, we provide a citation analysis of memetic studies. Theoretical directions of memetics in the informational context are outlined and developed. We outline two main discussion spaces, survey theoretical interests and describe where and when information is important to memetic discussion. We also find that there are continuities in goals which connect Dawkins’s meme with internet meme studies.Originality/valueTo our knowledge, this is the broadest, most inclusive review of memetics conducted, making use of a unique approach to studying information-oriented discourse across a corpus. In doing so, we provide information researchers areas in which they might contribute theoretical clarity in diverse memetic approaches. Additionally, we borrow the notion of “conceptual troublemakers” to contribute a corpus collection strategy which might be valuable for future literature reviews with conceptual difficulties arising from interdisciplinary study.

Routing and Scheduling in Multigraphs With Time Constraints—A Memetic Approach for Airport Ground Movement

Routing and scheduling problems with increasingly realistic modelling approaches often entail the consideration of multiple objectives, time constraints, and modelling the system as a multigraph. This detailed modelling approach has increased computational complexity and may also lead to violation of the additivity property of the costs. In the worst scenario, increased complexity makes the problem intractable for exact algorithms. Even when the problem is solvable, exact algorithms may not provide solutions within the given time budget, and the found solutions are not guaranteed to be optimal due to the additivity property violation. Approximate solution methods become more suitable in this case. This paper focuses on one particular real-world application, the Airport Ground Movement Problem, where both time constraints and parallel arcs are involved. We introduce a novel Memetic Algorithm for Routing in Multigraphs with Time constraints (MARMT) and present a comprehensive study of its different variants based on diverse genetic representation methods. We propose a local search operator that enhances search efficiency and effectiveness. MARMT is tested on real data based on two airports of different sizes. Our results show that MARMT does not suffer from the non-additivity property problem as it outperforms the state-of-the-art exact algorithm when allowed to converge. When a time budget of 10 seconds is imposed on MARMT, it is able to provide solutions with quality comparable (within 1-5% degradation) to the ones given by the exact algorithm with respect to the aggregated objective values. MARMT can be adapted for other applications, such as train operations.

A Brief History of Memetic Advertising from Trade Cards to the Internet

Abstract: Internet memes have become such a prevalent aspect of contemporary social media communication that brands have begun to use them as vehicles for advertising. However, the concept of a meme predates its colloquial understanding as an internet-based artifact. Advertisers have been creating memes—and conversely, incorporated memes into advertisements—for longer than these modern technologies and platforms have existed. This original historical account applies memetic theory to a selection of advertising forms, campaigns, and influential individuals throughout modern history in an effort to trace the relationship between memes and advertising from the early seventeenth century to the dawn of the internet era. Of specific interest in this history is how advertisers and creators have relied upon memetic processes of imitation and transformation to maximize advertising effectiveness, memorability, and longevity through consumers' existing knowledge of content and form. Though necessarily limited in scope, this account provides a first step toward documenting how advertisers have implemented memetic approaches over time and how they inform current internet-based memetic advertising practice.

It’s not rocket science: on the birth and propagation of the idiom

The present study relies on the five-stage model of phraseme genesis (Villers [2018; 2022]) in its exploration of the birth and propagation of a phraseological unit (PU). The focus is limited to the category of idioms, which represent a subclass of PUs (Moon [1998]; Everaert et al. [1995: 4]; Mel’čuk [1995: 168]). The choice of the idiom it’s not rocket science was motivated by earlier research on phraseme genesis (Villers [2016; 2022]) which suggests that phases such as birth and propagation are easier to study in newer phrasemes, and rocket science, or the science of designing spacecraft, is of a more recent date. The study combines the corpus-based and memetic approach, and it has a twofold aim. The first objective is to ascertain the birth of the idiom, which is done by contrasting the data provided by COCA and Google Books N-gram Viewer. The second objective is to determine its main media of propagation. This is explored with the help of COCA which provides the information on the distribution of the idiom across different genres. In order to uncover the reasons behind the successful genesis of the idiom, we also check the features (i.e. propagation boosters) such as distinctiveness, novelty, veracity, utility, ornatus, and publicity. The results highlight the limitations of online corpora such as COCA and Google Books when it comes to the origin and propagating agents of new phrasemes given that there were no matching records for the earliest use of the idiom that is readily accessible on the Internet (that is, the year 1985). Rather, the corpora suggest that the idiom gained currency in 1987, and was first used in a magazine. Based on the observed data, the successful propagation of the idiom is largely due to its intrinsic qualities (distinctiveness, ornatus, veracity, and utility), the features that focus on the host’s point of view (novelty and expressivity), as well as its reliance on various propagation agents (the web, TV, movies, blog). The paper ends with the schematic representation of the phraseme genesis for the idiom under consideration. The study also shows that the model of phrase genesis can be used with equal ease to study these phases in idioms, but that the trace of the origin of a phraseme should be done by consulting more than one source.

A Memetic Approach to Multi-Disciplinary Design and Numerical Optimization Problems using Intensify Slime Mould Optimizer

A Memetic Approach to Multi-Disciplinary Design and Numerical Optimization Problems using Intensify Slime Mould Optimizer

A memetic approach for optimizing software effort estimation using anti-predatory NIA

A memetic approach for optimizing software effort estimation using anti-predatory NIA

APPLYING MEMETIC APPROACH IN ENGLISH WRITING TEACHING WITH INTERNET PLUS TOOLS: AN EXPLANATORY RESEARCH

This research explores the application of the memetic approach in teaching English writing through the Internet plus tools. The study aims to provide an in-depth understanding of the effectiveness of this approach on students' writing performance, their attitudes towards writing, and their motivation to learn English. The study is conducted through explanatory research, which combines both qualitative and quantitative research methods. The data is collected through surveys, interviews, and observations of students' writing performances before and after the intervention. The results of the study suggest that the use of a memetic approach in English writing teaching with Internet plus tools had a positive impact on EFL students' writing proficiency. The students reported that the use of the internet plus tools made writing more engaging, and the memetic approach helped them understand the cultural and social contexts of writing. The findings also indicate that the student’s writing skills significantly improved after the intervention. This research provides valuable insights into the use of a memetic approach in teaching English writing and highlights the potential benefits of internet-plus tools in enhancing the students' learning experiences.

Inspirational Insights: ‘Ecosystems’ and ‘Mind Viruses’ in Folklore Research: Does Folkloristics Need Memetics?

Abstract The paper deals with applicability of the ‘memetic approach’ and ‘epidemiology of culture’ in present day folklore research. These theoretical models could be supplemented by certain ideas and hypotheses borrowed from actor-network theory and the cognitive science of religion. The development of contemporary folkloristic theorising could proceed from a new experimental ethnography that would combine memory and narrative studies, cognitive research and the theory of memes with more common or habitual methods of folklore research and cultural anthropology.

The Meme’s-Eye View of Strategic Communication: A Case Study of Social Movements from a Memetic Perspective

ABSTRACT The article argues that a memetic approach, or meme’s-eye view, could help bring together the strategic management view and the CCO-school. ‘Memes’ are understood as a second-order concept, i.e., as a reference to ‘memory traces’ in people’s minds and anchor-point of joint or collective intentionality. This view, it is argued, permits the conceptualization of communication as a resource. To illustrate, two cases are analyzed: 1) the Montagsdemos in the former German Democratic Republic (GDR) with its core meme Wir sind das Volk (We are the people); 2) the so-called ‘Satanic Panic’ and the QAnon movement with its ‘Save the Children'-meme’. The analysis illustrates how memes endure and resurface in new and different environments. In conclusion, the article proposes that the shift to memetic population dynamics allows strategic communication-researchers to reformulate often unanswerable questions (“What does the strategic actor want?”) into more operationalizable ones (“What memes are launched? How are they constructed?”).

Memetic search for the minmax multiple traveling salesman problem with single and multiple depots

The minmax multiple traveling salesman problem with single depot (the minmax mTSP) or multiple depots (the minmax multidepot mTSP) aims to minimize the longest tour among a set of tours. These two minmax problems are useful for a variety of real-life applications and typically studied separately in the literature. We propose a unified memetic approach to solving both cases of the minmax mTSP and the minmax multidepot mTSP. The proposed algorithm features a generalized edge assembly crossover to generate offspring solutions, an efficient variable neighborhood descent to ensure local optimization as well as an aggressive post-optimization for additional solution improvement. Extensive experimental results on 77 minmax mTSP benchmark instances and 43 minmax multidepot mTSP instances commonly used in the literature indicate a high performance of the algorithm compared to the leading algorithms. Additional experimental investigations are conducted to shed light on the rationality of the key algorithmic ingredients.

Multi‐objective memetic approach for the optimal web services composition

AbstractService composition is the process of combining a set of elementary or atomic services. The aim is to produce a new composite service to satisfy the user's request that cannot be satisfied by the atomic services. Combining multiple services is a complex problem that has been the subject of several research studies. The meta‐heuristic approaches are good techniques that have been used to solve several complex problems in various domains. These techniques are able to discover promising search regions and locate good quality solutions in reasonable time without exploring the whole solution space. In this paper, we deal with the problem of optimal web service composition by using meta‐heuristic approaches. Given a set of services and a set of tasks to be completed, the problem is to find the best set of services composition to complete all tasks where each service must be assigned to a given task. This problem can be modelled as a combinatorial optimization problem with a set of objective functions that need to be optimized. We search for a composite service that allows us to execute the considered tasks and offers the best quality of services (QoS). More precisely, we search for an execution plan that indicates for each task the assigned service. First, we propose a multi‐objective local search based meta‐heuristic (MO‐LS) and a multi‐objective genetic algorithm (MO‐GA) to handle our problem. Then we propose a multi‐objective memetic algorithm (MO‐MA) that combines the two methods LS and GA. The role of GA is to detect promising regions to be explored. The role of LS is to exploit efficiently the potential regions created by GA. Four objective functions are used to compute the Pareto optimal set of solutions. The main objective is to minimize cost and time and to maximize availability and reputation and produce a good composite service. The three proposed approaches namely MO‐LS, MO‐GA, and MO‐MA are evaluated on some datasets generated randomly and on the well‐known QWS dataset to select the best fit services in terms of maximum or minimum aggregated end‐to‐end QoS parameters. The numerical results are encouraging and demonstrate the effectiveness of the proposed MO‐MA for the web service composition.

Memetic EDA-Based Approaches to QoS-Aware Fully Automated Semantic Web Service Composition

Comprehensive quality-aware automated semantic web service composition is an NP-hard problem, where service composition workflows are unknown, and comprehensive quality, i.e., Quality of services (QoS) and Quality of semantic matchmaking (QoSM) are simultaneously optimized. The objective of this problem is to find a solution with optimized or near-optimized overall QoS and QoSM within polynomial time over a service request. In this paper, we proposed novel memetic EDA-based approaches to tackle this problem. The proposed method investigates the effectiveness of several neighborhood structures of composite services by proposing domain-dependent local search operators. Apart from that, a joint strategy of the local search procedure is proposed to integrate with a modified EDA to reduce the overall computation time of our memetic approach. To better demonstrate the effectiveness and scalability of our approach, we create a more challenging, augmented version of the service composition benchmark based on WSC-08 \cite{bansal2008wsc} and WSC-09 \cite{kona2009wsc}. Experimental results on this benchmark show that one of our proposed memetic EDA-based approach (i.e., MEEDA-LOP) significantly outperforms existing state-of-the-art algorithms.

SPMS-ALS: A Single-Point Memetic structure with accelerated local search for instance reduction

• SPMS-ALS is a single-point memetic structure for instance reduction. • SPMS-ALS proposes a domain specific accelerated local search based on Pattern Search. • SPMS-ALS is a memetic approach designed according to a bottom-up strategy. • SPMS-ALS can save up to 85% of the runtime and yet achieves an excellent performance. Real-world optimisation problems pose domain specific challenges that often require an ad-hoc algorithmic design to be efficiently addressed. The present paper investigates the optimisation of a key stage in data mining, known as instance reduction, which aims to shrink the input data prior to applying a learning algorithm. Performing a smart selection or creation of a reduced number of samples that represent the original data may become a complex large-scale optimisation problem, characterised by a computationally expensive objective function, which has been often tackled by sophisticated population-based metaheuristics that suffer from a high runtime. Instead, by following the Ockham’s Razor in Memetic Computing, we propose a Memetic Computing approach that we refer to as fast Single-Point Memetic Structure with Accelerated Local Search (SPMS-ALS). Using the k-nearest neighbours algorithm as base classifier, we first employ a simple local search for large-scale problems that exploits the search logic of Pattern Search, perturbing an n -dimensional vector along the directions identified by its design variables one by one. This point-by-point perturbation mechanism allows us to design a strategy to re-use most of the calculations previously made to compute the objective function of a candidate solution. The proposed Accelerated Local Search is integrated within a single-point memetic framework and coupled with a resampling mechanism and a crossover. A thorough experimental analysis shows that SPMS-ALS, despite its simplicity, displays an excellent performance which is as good as that of the state-of-the-art while reducing up to approximately 85% of the runtime with respect to any other algorithm that performs the same number of function calls.

Solving the Multiple Traveling Salesman Problem Using Memetic Algorithm

The Multiple Traveling Salesman Problem (MTSP) is considered as an NP-complete problem due to the difficulty of finding the shortest tour between different cities with a set of constraints such as visiting each city once by one salesman. The solution tour represents the sum of all tours' costs performed by n salesmen. In this research, we propose a novel approach to find different solutions for various instances of MTSP based on a memetic algorithm using Genetic Algorithm (GA) and Hill-Climbing (HC) algorithm. The experimental results proved that the memetic approach achieved promising results i.e., minimum total tour compared to other existing approaches.

ИСПОЛЬЗОВАНИЕ МЕМЕТИКИ ПРИ ИССЛЕДОВАНИИ РЕЦЕПЦИИ АНТИЧНОСТИ В АМЕРИКАНСКОЙ ПРЕССЕ РУБЕЖА XIX−XXВЕКОВ

Antiquity, which once inspired the Founding Fathers and later became an important reference point for many subsequent generations of American politicians, has lost its former significance. Many researchers traditionally associate this process with the industrialization at the turn of the 19th and 20th century, when society placed more emphasis on practical knowledge and skills. It would be logical to anticipate a gradual decrease in the number of references to Ancient Greek and Roman history featured in the publications of the emerging mass press focused on the needs of a wide audience and consisting of short and catchy notes. However, there was an upsurge of interest in antiquity in American newspapers. Unfortunately, researchers of classical reception usually pay little attention to periodicals. Using the memetic approach, the article attempts to resolve this contradiction. In addition, the survey analyzes which particular classical subjects were interesting to the readers of mass press, and considers possible options for interpreting and rethinking some ancient history’s images. Through a range of public issues, as well as events and characters of ancient history, the article examines two subjects in detail: the fall of Rome and Cornelia, mother of the Gracchi.

«Экосистемы сюжетов»: эмоциональные и когнитивные модели в современной фольклористике

The article deals with one of the central problems of folklore research, the problem of semantic and syntagmatic stability of narrative plots. Infuential 20th-century theories of folklore have not provided us with a clear and consistent solution. New perspectives for understanding of these processes could be discussed in the context of the ‘meme theory’. In the perspective of memetic approach, viability of tale types is determined by their ‘cognitive adaptability’ and social relevance, rather than stable semantics or ‘historical roots’. Examples from present day popular culture, including the dissemination of the so-called ‘happiness cakes’, seem to point towards a certain symbiosis of memes and biological entities. The paper considers elaboration of memetic approach to culture in relation to the actor-network theory, anthropology of emotions, and cognitive science.

Memetic coral reefs optimization algorithms for optimal geometrical design of submerged arches

This paper deals with the geometrically nonlinear analysis of submerged arches by means of memetic Coral Reefs Optimization algorithms. The classic design of submerged arches is only focused on calculating the bending stress-less shape (funicular shape) of the structure. Nevertheless, recent works show that this funicular shape can be approached by using a parametric family curve, which also allows a multi-variable optimization of the arch’s geometry. Using this novel parametric set of curves, we propose a new Coral Reefs Optimization (CRO) algorithm based on a memetic approach to tackle the geometrically nonlinear design of submerged arches. Specifically, the proposed CRO approaches have been tested with different search procedures as exploration operators, and we also test a multi-method version of the algorithm, the Coral Reefs Optimization with Substrate Layers (CRO-SL), which considers several search procedures within the same evolutionary population. A local search to improve the solutions has been considered in all cases, to obtain powerful memetic operators for this problem. It is also shown how the different memetic versions of the CRO (specially those involving multi-methods and Differential Evolution search procedures), together with the parametric encoding, are able to obtain nearly-optimal geometries for underwater installations. The performance of the proposed algorithm has been compared with state-of-the-art algorithms for optimization: L-SHADE and HCLPSO. Statistical tests have carried out with the aim of comparing the results. It is shown that there is not significant differences between the proposed results by the three algorithms.

Cluster-Based Memetic Approach of Image Alignment

The paper presents a new memetic, cluster-based methodology for image registration in case of geometric perturbation model involving translation, rotation and scaling. The methodology consists of two stages. First, using the sets of the object pixels belonging to the target image and to the sensed image respectively, the boundaries of the search space are computed. Next, the registration mechanism residing in a hybridization between a version of firefly population-based search procedure and the two membered evolutionary strategy computed on clustered data is applied. In addition, a procedure designed to deal with the premature convergence problem is embedded. The fitness to be maximized by the memetic algorithm is defined by the Dice coefficient, a function implemented to evaluate the similarity between pairs of binary images. The proposed methodology is applied on both binary and monochrome images. In case of monochrome images, a preprocessing step aiming the binarization of the inputs is considered before the registration. The quality of the proposed approach is measured in terms of accuracy and efficiency. The success rate based on Dice coefficient, normalized mutual information measures, and signal-to-noise ratio are used to establish the accuracy of the obtained algorithm, while the efficiency is evaluated by the run time function.