Evolutionary Planning Research Articles

An evolutionary planning method for distribution networks considering prosumers and shared energy storage

An evolutionary planning method for distribution networks considering prosumers and shared energy storage

Iran’s Participatory Power Market Regarding Distributed Generation from Renewable Sources: A Case Study

To study initial conditions for participatory power market formation based on renewable energy sources (RES) in Iran after complete accomplishment of the economic evolutionary plan, a case study for a residential building has been conducted to consider the effects of the most important parameters. So, a model of power market including three parts: consumption, production and regulations, has been optimized to achieve to a micro cost effective system of participatory power market regarding distributed generation from RES. The results indicate that the power tariff structure and rates, RES technology capital cost and economic conditions are prominent parameters. As well, to initiate the power market, a revised power tariff structure and rates are suggested; namely, a plan for shifting peak load hours from evening to day hours is essential. Also, it is demonstrated that the policy of establishing a participatory power market included photovoltaic distributed generation systems must be pursued in the economic evolutionary plan with emphasis on development of zero energy cost buildings.

Tackling Erosion in Variant-Rich Software Systems: Challenges and Approaches

Software product lines (SPL) have emerged as a pivotal paradigm in software engineering, enabling the efficient development of variant-rich software systems. Consistently updating these systems, often through over-the-air updates, enables the continuous integration of new features and bug fixes, ensuring the system remains up to date throughout its entire lifecycle. However, evolving such complex systems is an error prone task, leading to a phenomenon known as erosion. This phenomenon significantly impacts the efficiency and longevity of software systems, presenting a formidable challenge for manufacturers of variant-rich software systems, such as in the automotive domain. While existing studies concentrate on the evolutionary planning of variant-rich software systems, there is a noticeable lack of research addressing the problem of erosion. In this paper, we conduct an in-depth exploration of the erosion phenomena within variant-rich software systems. We begin by highlighting the significance of controlling erosion in extensive variant-rich software systems. Subsequently, we address the current challenges regarding tackling erosion, including issues such as the lack of a consensus on understanding and defining erosion, as well as the early detection and elimination. Finally, we outline a first approach aimed at tackling erosion in variant-rich software systems.

Novel evolutionary planning technique for flexible-grid transmission in optical networks

This paper proposes a novel joint resource allocation technique for flexible-grid systems by utilizing non-dominant sort genetic algorithm (NSGA-II) in a multi-objective optimization framework. It pioneers the implementation of an evolutionary mechanism to optimize resources as means of mitigation of physical layer impairments. This investigation initially introduces a proposal in which bandwidth reduction, maximization of the minimum signal-to-noise ratio (SNR) margin, and minimization/maximization of the sum of SNR margins are studied under dual-objective Pareto analysis in the link-level scenario. Later, the technique extends existing provisioning strategies for network planning by targeting the reduction of blocking and spectral utilization of optical connections.

New insights into the processes of biological evolution and human reproduction provided through a dialogue between science and Qur’an

In this paper I present new insights into the processes of biological evolution and human reproduction in the light of a dialogue between the current scientific knowledge and Qur‟an verses. I demonstrate how this dialogue could provide new complementary information and a more comprehensive state of each of these two processes. After clearing up some confusions and uncertainties related to the biological evolution process I propose a new vision for this process considering that the Creator (Allah) of the entire Universe had organized and supervised the emergence of living beings depending on a wonderful evolutionary plan. As this vision is hopefully in agreement with my interpretations of related Qur‟an verses, I concretize it from them. One of scientific paintings deduced from these verses shows how our humankind emerged at the top of a complex network of evolutionary stages evolved from the earth like the emergence of the upper part of the top of a tree. To the second biological process „Human Reproduction‟ Allah gives a more accurate designation „Human Picturing Creation‟ insisting on the fact that the major acts of this process do not happen randomly but under His supervision. Moreover Allah given to the major elements of this process, wonderful designations including some unnoticed details through superb rhetoric formats peculiar to Qur‟an. At the end of this paper I point out that my interpretations of Qur‟an verses, based on new rigorous methodology, are generally different from the existing ones showing how the latter include errors and distortions making them incompatible with science. More bad consequences, such as terrorism, have been the result of erroneous interpretations of some verses on socio-political issues. To solve this problem of erroneous interpretations and related false considerations that have accumulated through the ages and were merged into cultures of Muslim societies, I call for a “First International Real Renewal of Islam”
 Key words: Qur‟an interpretation, Biological evolution, Supernatural Creator, Limits of science, Human reproduction, Picturing creation, Human gametes, Human zygote, Human embryogenesis, Real Renewal of Islam.

Diversity Maintenance for Efficient Robot Path Planning

Path planning is present in many areas, such as robotics, video games, and unmanned autonomous vehicles. In the case of robots, it is a primary low-level prerequisite for the successful execution of high-level tasks. It is a known and difficult problem to solve, especially in terms of finding optimal paths for robots working in complex environments. Recently, population-based methods for multi-objective optimization, i.e., swarm and evolutionary algorithms successfully perform on different path planning problems. Knowing the nature of the problem is hard for optimization algorithms, it is expected that population-based algorithms might benefit from some kind of diversity maintenance implementation. However, advantages and potential traps of implementing specific diversity maintenance methods into the evolutionary path planner have not been clearly spelled out and experimentally demonstrated. In this paper, we fill this gap and compare three diversity maintenance methods and their impact on the evolutionary planner for problems of different complexity. Crowding, fitness sharing, and novelty search are tailored to fit specific problems, implemented, and tested for two scenarios: mobile robot operating in a 2D maze, and 3 degrees of freedom (DOF) robot operating in a 3D environment including obstacles. Results indicate that the novelty search outperforms the other two methods for problem domains of higher complexity.

Minimum Time Search in Real-World Scenarios Using Multiple UAVs with Onboard Orientable Cameras

This paper proposes a new evolutionary planner to determine the trajectories of several Unmanned Aerial Vehicles (UAVs) and the scan direction of their cameras for minimizing the expected detection time of a nondeterministically moving target of uncertain initial location. To achieve this, the planner can reorient the UAVs cameras and modify the UAVs heading, speed, and height with the purpose of making the UAV reach and the camera observe faster the areas with high probability of target presence. Besides, the planner uses a digital elevation model of the search region to capture its influence on the camera likelihood (changing the footprint dimensions and the probability of detection) and to help the operator to construct the initial belief of target presence and target motion model. The planner also lets the operator include intelligence information in the initial target belief and motion model, in order to let him/her model real-world scenarios systematically. All these characteristics let the planner adapt the UAV trajectories and sensor poses to the requirements of minimum time search operations over real-world scenarios, as the results of the paper, obtained over 3 scenarios built with the modeling aid-tools of the planner, show.

Evolutionary Planning of Multi-UAV Search for Missing Tourists

In recent years, there have been increasing reports of missing tourists around the world. The use of unmanned aerial vehicles (UAVs) can significantly improve the performance of search and rescue operations. However, planning the search paths of UAVs can be a highly complex optimization problem, and one of the most challenging tasks in the problem formulation is the estimation of target location probability distribution over time. This paper presents a problem of scheduling multiple UAVs to search for missing tourists and proposes a method for estimating tourist location probabilities which change with topographic features, weather conditions, and time. To solve the problem efficiently, we propose a hybrid evolutionary algorithm which consists of the main algorithm and a sub-algorithm. The main algorithm uses specific migration and mutation operators to evolve a population of main solutions, and the sub-algorithm combines a problem-specific heuristic and tabu search method to optimize each UAV path. The experimental results on a wide variety of test instances (including five real-world instances) demonstrate the performance advantages of the proposed method.

Evolutionary MCTS with Flexible Search Horizon

In turn-based multi-action adversarial games each player turn consists of several atomic actions, resulting in an extremely high branching factor. Many strategy board, card, and video games fall into this category, which is currently best played by Evolutionary MCTS (EMCTS) -- searching a tree with nodes representing action sequences as genomes, and edges representing mutations of those genomes. However, regular EMCTS is unable to search beyond the current player's turn, leading to strategic short-sightedness. In this paper, we extend EMCTS to search to any given search depth beyond the current turn, using simple models of its own and the opponent's behavior. Experiments on the game Hero Academy show that this Flexible-Horizon EMCTS (FH-EMCTS) convincingly outperforms several baselines including regular EMCTS, Online Evolutionary Planning (OEP), and vanilla MCTS, at all tested numbers of atomic actions per turn. Additionally, the separate contributions of the behavior models and the flexible search horizon are analyzed.

Playing Multiaction Adversarial Games: Online Evolutionary Planning Versus Tree Search

We address the problem of playing turn-based multiaction adversarial games, which include many strategy games with extremely high branching factors as players take multiple actions each turn. This leads to the breakdown of standard tree search methods, including Monte Carlo tree search (MCTS), as they become unable to reach a sufficient depth in the game tree. In this paper, we introduce online evolutionary planning (OEP) to address this challenge, which searches for combinations of actions to perform during a single turn guided by a fitness function that evaluates the quality of a particular state. We compare OEP to different MCTS variations that constrain the exploration to deal with the high branching factor in the turn-based multiaction game Hero Academy . While the constrained MCTS variations outperform the vanilla MCTS implementation by a large margin, OEP is able to search the space of plans more efficiently than any of the tested tree search methods as it has a relative advantage when the number of actions per turn increases.

Business Performance Management Models Based on the Digital Corporation’s Paradigm

Digital development of the global economy has increasingly severe implications for business, society and State. The so-called digital transformation (DX) has already turned from a scientific paradigm to reality, adjusting the development strategies of entire states, changing the face of social infrastructure and reformatting business processes. The market participants now face serious challenges: how to build their own business model and how to find their place in the digital ecosystem of the nearest future, drawing on digital technologies. That is precisely why the research and approbation of approaches to building an information model of a digital corporation are not only topical, but also very timely. The article provides an overview of several important studies in the field of DX, along with a comparative analysis of classical and digital models of corporate governance; it also shows the potential for the development of the CPM concept (Corporate performance management) considering the DX requirements and the advantages of the evolutionary planning approach. The authors present the paradigm of building information and analytical systems for digital corporation management with the use of advanced business intelligence based on dynamic intellectual models. The article describes examples of real projects on the development of support systems for decision-making in terms of marketing and financial management, including business effects from the use of similar systems. The authors have summarized project experience in the field of building a digital system of corporate management based on the Academic Competence Center of IBM "Reasonable Commerce" (located in Plekhanov Russian University of Economics) and outlined the prospects for further research.

Study of Imbalance of Twisted Aluminum Oxide Yarns Under Twist Optimization Conditions

A regression equation that takes account of the dependence of imbalance of yarns with a 100 tex linear density on the first and second twist into two and then five strands, respectively, was derived by full factorial experiment. The optimum twists were obtained by evolutionary planning.

Evolutionary planning of virtualized cyber-physical compute and control clusters

Virtualization technology has the potential to notably advance the automation process in the domain of cyber-physical systems (CPS). It can improve both dependability and availability as well as significantly reduce the procurement, operation and maintenance costs of such systems. However, in the context of virtualization, research has put the most emphasis on topics of hardware utilization and fault-tolerance. There is little literature on how to model, integrate and consolidate a CPS by means of virtualization. In this paper we present a methodology for planning safe and efficient virtualized cyber-physical compute and control clusters execution platforms for time-constrained virtual machines (VMs) that encapsulate CPS applications. We discuss the used methods, describe the corresponding models and the required system architecture. In contrast to typical resource allocation problems from other domains (e.g. cloud computing), in this case, the planning process must take real-time requirements of applications into account. In order to achieve this, we combine evolutionary algorithms with formal system performance analysis in particular algorithms considered in classical scheduling theory. Such an approach allows not only to optimally dimension the compute and control clusters, but also provides strict guarantees regarding the timing predictability of the integrated CPS. Further, the embedment of a formal performance analysis technique notably eases the modeling of a system. As a consequence, the modeling process is fast, flexible and accessible not only to experts but also to system designers as they do not have to struggle with complex and time consuming mathematical formulations. Finally, our approach also provides answers to several practical questions that arise when integrating a CPS by means of virtualization.

Evolutionary Planning of Safe Ship Tracks in Restricted Visibility

The paper presents the continuation of the author's research on ship track planning by means of Evolutionary Algorithms (EA). The presented method uses EA to search for an optimal set of safe tracks for all ships involved in an encounter. Until now the method assumed good visibility – compliance with standard rules of the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS, 1972). However, in restricted visibility, when Rule 19 applies instead of Rules 11 to 18, the problem is a different one. Therefore this paper introduces the extended method, with a focus on compliance with Rule 19 and its implications. It includes descriptions of detecting, penalizing and eliminating violations of Rule 19. The method has been implemented and the paper contains sample results of computer simulation tests carried out for ship encounters in restricted visibility in both open and restricted waters. They confirm the effectiveness of the chosen approach and suggest that the method could be applied in on board decision support systems.

Sources’ Response for supplying energy of a residential load in the form of on-grid hybrid systems

Because of the nonrenewable conventional sources of energy and rising of energy prices, these kinds of energy sources are not responsible to meet increasing of demand any more. So the use of on-grid hybrid systems for their unique characteristics has increased. These forms of organizations would result in reducing of transmission losses, pollution and the ability to exert energy management. This report introduces an economic model for the fuel cell, photovoltaic panels and wind turbine. Three sources of energy beside the local grid can respond to all variations of demand. Since sources of energy should change their productions according to the demand variations, we call it sources’ response. The model consists of the cost of supplying energy, cost of recovered thermal energy from the fuel cell, wind turbine power production cost, solar power generation cost, cost of exchange power with the local grid and the cost of maintenance. Finally, it is trying to minimize total cost by the help of three different evolutionary planning methods. Encouraging results promise the use of hybrid systems in supplying residential load in near future.

Applying the Capability Maturity Model to Assurance of Learning

Assurance of Learning (AoL) focuses on the continuous improvement of curriculum development, program review, and, in many cases, accreditation. AoL programs are important for assessing undergraduate, masters, and/or doctoral degree programs, as well as the impact on curriculum management. A recent mandate from the Association to Advance Collegiate Schools of Business (AACSB) is the need for mature AoL processes to be in place. This paper describes the Capability Maturity Model (CMM) and discusses how it can be applied to assess the maturity and capability of any educational institution’s AoL initiative. An Aol-CMM model introduced and discussed in this paper can be used to assess an academic institution’s AoL maturity and then act as a road map to develop and align key processes to plan and advance to a higher level of AoL maturity. A set of AoL key processes at an AACSB accredited business school provides a backdrop and discussion to understand better the application of this CMM framework. This should be of interest and value since the model can be used by schools and programs with varying levels of process maturity and capability. Even institutions not interested in accreditation may find the application of a maturity model useful for improving academic excellence. Regardless, each school or program can assess its current state and then develop an evolutionary plan to reach the next higher level of AoL process maturity.

How to Make Innovations Practical

Background/ContextA fundamental tension has long existed between school reform proposals and actual teaching practice. Despite a large literature on teacher change, the discontinuity between innovation and practice continues and many attempts to reform teaching fail to be enacted in most classrooms.Purpose/Objective/Research Question/Focus of StudyThe purpose of this paper is to present a bridging methodology for connecting pedagogical innovations to the practical demands of teaching. The methodology is framed within practicality theory, which is an ecologically grounded analysis of the design issues and constraints that practitioners face in the everyday work of teaching. To conduct lessons, teachers must construct procedures (instrumentality) that fit circumstances (congruence) within available time and resources (cost). Underlying these practicality dimensions is a set of reasoning processes that can be understood from the perspective of three strands of research on bounded rationality—goal systems, heuristics, and evolutionary planning.Intervention/Program/PracticeThe analysis of teacher practical reasoning provides a design foundation for a bridging methodology consisting of (a) construction of a heuristic goal system (HGS) representation of the hierarchy of goals and heuristic means that underlie a teacher's planning decisions with respect to lesson segments used to carry out instruction; and (b) a teaching impact analysis (TIA) that connects an innovation's lesson structure to a teacher's heuristic goal system and shows how a teacher can adapt his/her current practice to achieve increased expected value (i.e., an improvement).Research DesignThis study was designed as an analytical essay that theorizes teaching practice, teacher reasoning, and a bridging methodology for connecting teaching practice with specific educational innovations. Cases of an experienced biology teacher and of 11 student teachers are presented that demonstrate the nature of this bridging methodology and variations in its use in particular circumstances.Conclusions/RecommendationsThe bridging framework provides a practical tool for identifying the action-guiding model of a teacher, the connection of this model to the precise components of an innovation, and the recombination or adaptations a teacher can make to achieve personal goals through an innovation. Although further studies are needed, this framework promises to furnish a powerful tool for making innovations practical. We cannot characterise behaviour independently of intentions, and we cannot characterise intentions independently of the settings which make those intentions intelligible both to agents themselves and to others (MacIntyre, 1981, p. 192).

Effective Governance of Global Financial Markets: an Evolutionary Plan for Reform

AbstractTwo questions remain widely open when it comes to global financial markets. First, what is the raison d'être of open global markets? Second, is it possible to foster open markets without an international governance structure supervising them? Post‐crisis regulatory reform presents an acute paradox. While the content of international financial regulation is changing rapidly, the reform of governance structures is painfully slow. There is no formal governance structure dealing with cross‐border supervision of global financial institutions. In addition, there is no crystallized institutional capacity at the international level dealing with cross‐border crises and the resolution of global institutions. Other areas of concern are the global supervision of systemic risk and the absence of a reliable finance research watchdog dealing with the production of regulatory standards. This article outlines an international governance framework to deal effectively with these concerns. The adoption of the proposed plan would lead to breaking down the territorial link in the supervision of large financial institutions and of systemic risk, without causing intolerable loss of sovereignty. In addition, the proposed structure is premised on a set of explicit values. These would provide a strong signal to global markets that they need to shift their focus from speculation to development goals.

On the performance comparison of multi-objective evolutionary UAV path planners

The big number of evolutionary planners for Unmanned Aerial Vehicles (UAVs) that have been developed demonstrates the good acceptance that the evolutionary techniques enjoy within the UAV community. However, the minor or nonexistent statistical characterization of the results obtained by the majority of the planners not only makes it difficult to assess their actual performance but also to justify the selection and/or parameterization of their supporting algorithms. To fill the gap, this paper proposes a method for comparing the planners performance by jointly employing several general and problem-specific quality indexes, which take into account the complexity and particularities of the problem. The generality of the performance metrics adopted, which are able to deal with any multi-objective dominance definition, makes them equally applicable to multi-objective planners with different relation operations (such as Pareto dominance, weighted objectives aggregation, and others). The specificity of the other indexes, which consider the types of solutions preferred by the problem experts, makes them especially attractive to characterize their planners’ behavior. The paper also shows how to analyze the results of the quality indexes graphically in order to identify, for a particular UAV planning problem, the best planners within a set of 36 variants (based on Genetic Algorithms, Particle Swarm Optimization and Differential Evolution).

Optimization of the twists of double-twisted high-melting fibers

Ceramic fibers produced in the form of multi-filament filament fibers are not strong enough to be used directly as a structural material. Factorial experiment planning is used to obtain a regression equation that describes the dependence of the absolute breaking load of a filament with a linear density of 100 tex on the degree of twisting when the initial 10-tex filament is doubled to form two strands and then five strands. The optimum degree of twisting is determined through the use of evolutionary planning.