The paper presents a method of priority scheduling that is useful during the planning of multiple-structure construction projects. This approach is an extension of the concept of interactive scheduling. In priority scheduling, it is the planner that can determine how important each of the technological and organisational constraints are to them. A planner's preferences can be defined through developing a ranking list that defines which constraints are the most important, and those whose completion can come second. The planner will be able to model the constraints that appear at a construction site more flexibly. The article presents a general linear programming model of the planning of multiple-structure construction projects, as well as various values of each of the parameters that allow us to obtain different planning effects. The proposed model has been implemented in a computer program and its effectiveness has been presented on a calculation example.

In this paper we present results of systematic and comprehensive simulation analysis of the Tsao & Safonov unfalsified controller for complex robot manipulators. In particular, we show that the controller falsification procedure yields the closedloop unfalsified controller, which accomplishes the control objective, within a finite and relatively short time interval with the number of invocations of linear programming based unfalsified controller selection procedure being relatively small. We also present some conclusions resulting from the investigation of the effect of such elements as manipulator structure complexity, prior knowledge about disturbances, reference trajectory and assigned closed-loop spectrum on unfalsified controller performance and computational complexity.

A new soft-fault diagnosis approach for analog circuits with parameter tolerance is proposed in this paper. The approach uses the fuzzy nonlinear programming (FNLP) concept to diagnose an analog circuit under test quantitatively. Node-voltage incremental equations, as constraints of FNLP equation, are built based on the sensitivity analysis. Through evaluating the parameters deviations from the solution of the FNLP equation, it enables us to state whether the actual parameters are within tolerance ranges or some components are faulty. Examples illustrate the proposed approach and show its effectiveness.

Positively invariant sets play an important role in the theory and applications of dynamical systems. The stability in the sense of Lyapunov of the equilibrium x = 0 is equivalent to the existence of the ellipsoidal positively invariant sets. The constraints on the state and control vectors of dynamical systems can be formulated as polyhedral positively invariant sets in practical engineering problems. Numerical checking method of positive invariance of polyhedral sets is addressed in this paper. The validation of the positively invariant sets can be done by solving LPs which can be easily done numerically. It is illustrated by examples that our checking method is effective. Compared with the now existing algebraic methods, numerical checking method is an attractive method in that it’s easy to be implemented.

The presented method is constructed for optimum scheduling in production lines with parallel

machines and without intermediate buffers. The production system simultaneously

performs operations on various types of products. Multi-option products were taken into

account – products of a given type may differ in terms of details. This allows providing for

individual requirements of the customers. The one-level approach to scheduling for multioption

products is presented. The integer programming is used in the method – optimum

solutions are determined: the shortest schedules for multi-option products. Due to the lack

of the intermediate buffers, two possibilities are taken into account: no-wait scheduling,

possibility of the machines being blocked by products awaiting further operations. These two

types of organizing the flow through the production line were compared using computational

experiments, the results of which are presented in the paper.

Current networks are designed for peak loads leading to low utilization of power resources. In order to solve this problem, a heuristic energy-saving virtual network embedding algorithm based on the Katz centrality (Katz-VNE) is proposed. For solving an energy-saving virtual network embedding problem, we introduce the Katz centrality to represent the node influence. In order to minimize the energy consumption of the substrate network, the energy-saving virtual network embedding problem is formulated as an integer linear program, and the Katz-VNE is used to solve this problem. The Katz-VNE tries to embed the virtual nodes onto the substrate nodes with high Katz centrality, which is effective, and uses the shortest paths offering the best factor of bandwidths to avoid the hot nodes. The simulation results demonstrate that the long-term average energy consumption of the substrate network is reduced significantly, and the long-term revenue/cost ratio, the acceptance rate of virtual network requests, and the hibernation rate of substrate nodes as well as links are improved significantly.