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• EVOLVABLE ADAS: H-GQM S.M.A.R.T.E.S.T. APPROACH

  D.E. Chickrin, А. А. Egorchev, D.V. Ermakov

  2020-07-20

  Abstract ▼

  The introduction to the mass market of vehicles with an ADAS 3+ level of automation is expected
  in the early 2020s. Currently, the vast majority of automakers conduct research in this
  field, a fairly large number of prototypes, pre-production and production systems have already
  been demonstrated. ADAS (advanced driver assistance systems) are complex hardware & software
  systems, the feature of which is that the core hardware platform remains unchanged for one or
  even several generations of vehicles (5–7 years). At the same time, the system should be able to
  transform and evolve to correct errors and expand functionality, especially due to active development
  of sensory peripheral systems and software algorithms. The GQM methodology and its modifications
  are used to support the development process of complex systems and evaluate them.
  However, these methodologies are limited exclusively to software products. Also, authors of these
  methodologies are not addressing explicitly the issues of applying the GQM methodology for analyzing
  and tracking the process of evolution of complex technical systems. This paper presents HGQM
  (Hardware GQM) methodology for controllable evolution of complex automotive hardware
  & software systems. The H-GQM methodology is based on GQM and is aimed at hardwaresoftware
  systems with a monolithic hardware core, a modifiable software core and atomic peripherals.
  Entity harmonization process is described to prove the applicability of the GQM for software-
  and-hardware systems analysis. S.M.A.R.T.E.S.T goal-setting concept is proposed for choice
  of evolutionary goals. This concept is based on S.M.A.R.T. criteria for the setting objectives of
  business processes and extended with harmonization and evolvability restrictions. The formulation
  of the H-GQM plan framework is provided using ADAS as an example. Within the framework of
  the proposed methodology, an ADAS-specific scalable target template has been formed.

• SOLUTIONS’ ENCODING IN EVOLUTIONARY METHODS FOR INSTRUMENTAL DESIGN PLATFORM

  E.V. Kuliev, А. А. Lezhebokov, М. М. Semenova, V.A. Semenov

  2020-07-20

  Abstract ▼

  The article considers current issues and analyzes the problems of three-dimensional integration
  and three-dimensional modeling that arise at the design stage during the solution of the
  problem of optimal planning of components of large and extra-large integrated circuits and case
  devices of electronic computing equipment. The main advantages of applying the principles of
  three-dimensional integration are presented and described in sufficient detail, which allow efficiently
  organizing the production of personalized electronics, optimally planning the configuration
  of large and ultra-large integrated circuits, taking into account thermal and energy characteristics.
  In the course of research, the authors developed an approach to encoding decisions based on
  an intelligent mechanism, which is characterized by the presence of built-in means of control of
  acceptable decisions. One of such tools that have experimentally proven their effectiveness is the
  built-in mechanism of “deadly mutations”, which takes into account the status of genes and predetermined
  restrictions on the final configuration of the housing of the designed device. A series of
  general approaches and specific algorithms for solving the planning problem based on the results
  of research by the author's team and modern approaches to solving NP-complete problems are
  proposed. The most important practically significant result of the research of the indicated problem
  is the developed software and instrumental design platform in the modern cross-platform Java
  programming language. The selected development technology allows you to use all the main advantages
  of modern multi-core and multi-processor architectures, to use software multi-threading
  to implement parallel schemes for solving combinatorial problems. The software and tool platform
  has a user-friendly interface, which allows you to effectively manage the process of solving the
  problem of planning the components of large and ultra-large integrated circuits of threedimensional
  integration by visualizing key performance indicators of algorithms on graphs and in
  text statistics blocks. The developed application software made it possible to carry out a series of
  computational experiments based on random data sets, as well as on open-data boron benchmarks
  for such tasks. The results of experimental studies have confirmed the theoretical estimates of the
  time complexity and effectiveness of the proposed approaches and algorithms, including the genetic
  algorithm, which uses the new decision coding mechanism proposed in the work.

• DEVELOPMENT OF BIOHEURISTICS FOR CREATING AN INTELLECTUAL SUBSYSTEM FOR MAKING EFFECTIVE DECISIONS OF NP-HARD AND NP-DIFFICULT COMBINATORY-LOGICAL PROBLEMS ON GRAPHS

  D. V. Zaruba , E. V. Kuliev , D.Y. Zaporozhets , M. M. Semenova

  2021-11-14

  Abstract ▼

  The article is devoted to the solution of new topical problems that have arisen in the conditions
  of the modern development of information and nanometer technologies in the field of design,
  as well as the development of new innovative methods that provide effective solutions in polynomial
  time. The article deals with the problem of solving NP-hard problems. The description of the
  procedure for measuring the complexity of the problem is presented the features of NP-hard and
  NP-difficult combinatorial logic problems are described. The main differences between the tasks
  are presented, as well as the problems that one has to face when solving this type of task. The general
  decision-making scheme is presented, consisting of the problem formulation; decisionmaking;
  signal in automatic systems and feedback. At the second stage (formation and selection of
  solutions), the solution is based on a bioinspired algorithm for finding solutions to the traveling
  salesman problem. To solve this problem, a modified bioinspired algorithm based on the behaviorof an ant colony was developed. Unlike other optimization methods, metaheuristic algorithms can
  find global optimal solutions for problems where there are many local solutions due to their random
  nature. These reasons have led to the widespread use of such algorithms in solving various
  optimization problems. Bioinspired algorithms are becoming a new revolution in the field of solving
  optimization problems. The statement of the traveling salesman problem is presented, as well
  as the solution of the problem on the basis of the ant algorithm. Algorithms such as genetic algorithms
  and PSO can be very useful, but they still have some disadvantages in solving multimodal
  optimization problems. These algorithms can find optimal solutions regardless of the physical
  nature of the problem. In the framework of experimental studies, the analysis of the work of
  bioinspired algorithms was carried out: the algorithm of a flock of bats, the bacterial algorithm
  and the ant algorithm.