Prospects of a mathematical theory of human behavior in complex man-machine systems tasks

A hierarchy of human activities is derived by analyzing automobile driving in general terms. A structural description leads to a block diagram and a time-sharing computer analogy. The range of applicability of existing mathematical models is considered with respect to the hierarchy of human activities in actual complex tasks. Other mathematical tools so far not often applied to man machine systems are also discussed. The mathematical descriptions at least briefly considered here include utility, estimation, control, queueing, and fuzzy set theory as well as artificial intelligence techniques. Some thoughts are given as to how these methods might be integrated and how further work might be pursued

Controlling Complexity in Spatial Modelling

The present complexity approach is based on two assumptions: A1: measurability of deviations of outcomes with respect to reference values; A2 : extension of A1 to multi-set analysis. Complexity is then defined in terms of multi-set deviation compared to single-set ones; an interpretation is given in terms of information costs; examples show the relevance of the interpretation. As a useful by-product the explicit solution of the quadratic part of the discrete logistic ? one of the examples ? is derived; a set of pij-numbers is introduced, and a workable method for generating them exposed. Extensions are considered, in particular controllability. A further application is then proposed, namely to hypergraph conflict analysis, in particular conflict resolution. Many decisional conflicts at the spatial level can be axiomatised in this form; it is shown how the use of particular structures ? in the mathematical sense of that word ? of the problem allows of reducing greatly the degree of complexity of the problem, and hence the difficulty of finding a solution.Chaos, complexity, conflict, dynamics, hypergraphs, information

A multiple channel queueing model under an uncertain environment with multiclass arrivals for supplying demands in a cement industry

In recent years, cement consumption has increased in most Asian countries, including Malaysia. There are many factors which affect the supply of the increasing order demands in the cement industry, such as traffic congestion, logistics, weather and machine breakdowns. These factors hinder smooth and efficient supply, especially during periods of peak congestion at the main gate of the industry where queues occur as a result of inability to keep to the order deadlines. Basic elements, such as arrival and service rates, that cannot be predetermined must be considered under an uncertain environment. Solution approaches including conventional queueing techniques, scheduling models and simulations were unable to formulate the performance measures of the cement queueing system. Hence, a new procedure of fuzzy subset intervals is designed and embedded in a queuing model with the consideration of arrival and service rates. As a result, a multiple channel queueing model with multiclass arrivals, (M1, M2)/G/C/2Pr, under an uncertain environment is developed. The model is able to estimate the performance measures of arrival rates of bulk products for Class One and bag products for Class Two in the cement manufacturing queueing system. For the (M1, M2)/G/C/2Pr fuzzy queueing model, two defuzzification techniques, namely the Parametric Nonlinear Programming and Robust Ranking are used to convert fuzzy queues into crisp queues. This led to three proposed sub-models, which are sub-model 1, MCFQ-2Pr, sub-model 2, MCCQESR-2Pr and sub-model 3, MCCQ-GSR-2Pr. These models provide optimal crisp values for the performance measures. To estimate the performance of the whole system, an additional step is introduced through the TrMF-UF model utilizing a utility factor based on fuzzy subset intervals and the α-cut approach. Consequently, these models help decision-makers deal with order demands under an uncertain environment for the cement manufacturing industry and address the increasing quantities needed in future

Survey of traffic control schemes and error control schemes for ATM networks

Among the techniques proposed for B-ISDN transfer mode, ATM concept is considered to be the most promising transfer technique because of its flexibility and efficiency. This paper surveys and reviews a number of topics related to ATM networks. Those topics cover congestion control, provision of multiple classes of traffic, and error control. Due to the nature of ATM networks, those issues are far more challenging than in conventional networks. Sorne of the more promising solutions to those issues are surveyed, and the corresponding results on performance are summarized. Future research problems in ATM protocol aspect are also presented

Many-Objective Optimization of Non-Functional Attributes based on Refactoring of Software Models

Software quality estimation is a challenging and time-consuming activity, and models are crucial to face the complexity of such activity on modern software applications. In this context, software refactoring is a crucial activity within development life-cycles where requirements and functionalities rapidly evolve. One main challenge is that the improvement of distinctive quality attributes may require contrasting refactoring actions on software, as for trade-off between performance and reliability (or other non-functional attributes). In such cases, multi-objective optimization can provide the designer with a wider view on these trade-offs and, consequently, can lead to identify suitable refactoring actions that take into account independent or even competing objectives. In this paper, we present an approach that exploits NSGA-II as the genetic algorithm to search optimal Pareto frontiers for software refactoring while considering many objectives. We consider performance and reliability variations of a model alternative with respect to an initial model, the amount of performance antipatterns detected on the model alternative, and the architectural distance, which quantifies the effort to obtain a model alternative from the initial one. We applied our approach on two case studies: a Train Ticket Booking Service, and CoCoME. We observed that our approach is able to improve performance (by up to 42\%) while preserving or even improving the reliability (by up to 32\%) of generated model alternatives. We also observed that there exists an order of preference of refactoring actions among model alternatives. We can state that performance antipatterns confirmed their ability to improve performance of a subject model in the context of many-objective optimization. In addition, the metric that we adopted for the architectural distance seems to be suitable for estimating the refactoring effort.Comment: Accepted for publication in Information and Software Technologies. arXiv admin note: substantial text overlap with arXiv:2107.0612

Machine interference problem with fuzzy environment

Abstract Machine interference is a significant problem in many manufacturing system and client server computing. Machine interference problem involve many parameters like break down rate, service rate, machine production rate, etc. Due to uncontrollable factors parameters in the machine interference problem may be fuzzy. This paper, proposes a methodology for constructing system performance measures, where breakdown rate and service rate are trapezoidal fuzzy numbers. Function principle is used as arithmetic operations of fuzzy trapezoidal numbers. Numerical example is solved successfully to illustrate the validity of the proposed approach. Since the system characteristics being expressed as a fuzzy trapezoidal numbers more information is provided for used by Management. By extending the fuzzy environment, the fuzzy queues can be represented more accurately by using the proposed approach, and the analysis of results for such queuing model will be useful and significant for system designers and practitioners

Perceptionization of FM/FD/1 queuing model under various fuzzy numbers

We present a FM/FD/1 queuing model with unbounded limit under different fuzzy numbers. The arrival (landing) rate and service (administration) rate are thought to be fuzzy numbers such as triangular, trapezoidal and pentagonal fuzzy numbers. Because random event can only be observed in an uncertain manner, the fuzzy result of an uncertainty mapping is a fuzzy random variable. Consequently, it is conceivable to characterize the specific connection between randomness and fuzziness. The execution proportions of this lining miniature are fuzzified after that examined by utilizing α-cut estimations and DSW algorithm (Dong, Shah and Wong). Relating to different fuzzy numbers, the numerical precedents are delineated to test the attainability of this model (miniature). A comparative illustration corresponding to each fuzzy number is accomplished for various estimations of α

Simulation Modeling and Analysis of Adjustable Service-Rate Queueing Models that Incorporate Feedback Control

Research shows that in a system model, when the production rate is adjusted based on the number of items in queue, the nature of the model changes from an open-loop queueing system to a closed-loop feedback control system. Service-rate adjustment can be implemented in a discrete event simulation model, but the effect of this adjustment has not been thoroughly analyzed in the literature. This research considers the design of feedback signals to generate realistic simulation models of production system behavior. A series of simulation experiments is conducted to provide practical guidance for simulation modelers on how adding a service-rate adjustment feedback loop to a queueing system affects system performance

Model Development Of A Conwip System For Production Control In Multi-Stage Multiproduct Manufacturing Environments Consisting Of High-Runner And Low-Runner Product Families

Production control systems can be generally categorized as push or pull systems. In a push system, production is initiated at scheduled times, whereas in a pull system, production is initiated when a signal is received. However, there are limitations to each system. Push systems are controlled by observing throughput, which requires an estimation of system capacity. Inaccurate estimates can cause work-in-process (WIP) to increase beyond the limit. Pull systems require maintaining a small amount of WIP for each product family. Nevertheless, a large product mix may still result in a high WIP level. The aim of this research is to develop and investigate a new pull system (made up of several variants) known as a parallel constant work-in-process (CONWIP) system. In the systems, product families are classified into two classes (high-runner and low-runner) based on the demand of the product mix. Each class uses a CONWIP system, where production is initiated upon withdrawal of finished goods