Accelerating backtrack search with a best-first-search strategy
Achievable potential reductions in the method of Kojima et al. in the case of linear programming
Achieving Optimal Design of the Production Line With Obtainable Resource Capacity
ACS-TS: Train scheduling using ant colony system.
Active set and interior methods for nonlinear optimization.
Acyclic orientations with path constraints
Many well-known combinatorial optimization problems can be stated over the set of acyclic orientations of an undirected graph. For example, acyclic orientations with certain diameter constraints are closely related to the optimal solutions of the vertex coloring and frequency assignment problems. In this paper we introduce a linear programming formulation of acyclic orientations with path constraints, and discuss its use in the solution of the vertex coloring problem and some versions of the frequency...
Acyclic Orientations with Path Constraints
Many well-known combinatorial optimization problems can be stated over the set of acyclic orientations of an undirected graph. For example, acyclic orientations with certain diameter constraints are closely related to the optimal solutions of the vertex coloring and frequency assignment problems. In this paper we introduce a linear programming formulation of acyclic orientations with path constraints, and discuss its use in the solution of the vertex coloring problem and some versions of the frequency...
Adaptive bacterial foraging optimization.
Adaptive constraint reduction for training support vector machines.
Adaptive control for discrete-time Markov processes with unbounded costs: Discounted criterion
We study the adaptive control problem for discrete-time Markov control processes with Borel state and action spaces and possibly unbounded one-stage costs. The processes are given by recurrent equations with i.i.d. -valued random vectors whose density is unknown. Assuming observability of we propose the procedure of statistical estimation of that allows us to prove discounted asymptotic optimality of two types of adaptive policies used early for the processes with bounded costs.
Adaptive high gain observer extension and its application to bioprocess monitoring
The adaptive version of the high gain observer for the strictly triangular systems subjected to constant unknown disturbances is proposed here. The adaptive feature is necessary due to the fact that the unknown disturbance enters in a way that cannot be suppressed by the high gain technique. The developed observers are then applied to a culture of microorganism in a bioreactor, namely, to the model of the continuous culture of Spirulina maxima. It is a common practice that just the biomass (or substrate)...
Adaptive resource allocation to stochastic multimodal projects: a distributed platform implementation in Java
Adaptive thresholding technique for solving optimization problems on attainable sets of (max, min)-linear systems
This article develops a parametric method depend on threshold technique for solving some optimization problems on attainable sets of so called (max, min)-separable linear systems. The concept of attainable set for (max, min)-separable linear equation systems will be introduced. Properties of the attainable sets will be studied in detail. The (max, min) - separable linear equation systems, in which the function of unknown variable occur only on one side, will be consider. The main idea of the proposed...
Additivities in fuzzy coalition games with side-payments
The fuzzy coalition game theory brings a more realistic tools for the mathematical modelling of the negotiation process and its results. In this paper we limit our attention to the fuzzy extension of the simple model of coalition games with side-payments, and in the frame of this model we study one of the elementary concepts of the coalition game theory, namely its “additivities”, i. e., superadditivity, subadditivity and additivity in the strict sense. In the deterministic game theory these additivites...
Adjacent vertices of the all 0-1 programming polytope
Adjoint variable method for the study of combined active and passive magnetic shielding.
Admission controls for Erlang's loss system with service times distributed as a finite sum of exponential random variables.
Advances in model-based fault diagnosis with evolutionary algorithms and neural networks
Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, the classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as evolutionary algorithms and neural networks become more and more popular in industrial applications of fault diagnosis. The main objective of this paper is to present recent developments regarding the application of evolutionary algorithms and neural...
Advances in modelling of complex systems : preface to the special issue
Advances in Modelling of Complex Systems : Preface to the Special Issue