Jonas Mockus

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The traditional numerical analysis considers optimization algorithms which guarantee some accuracy for all functions to be optimized. This includes the exact algorithms. Limiting the maximal error requires a computational effort that in many cases increases exponentially with the size of the problem (Horst and Pardalos, 1995, Handbook of Global(More)
Gap-junction (GJ) channels formed of connexin (Cx) proteins provide a direct pathway for electrical and metabolic cell-cell interaction. Each hemichannel in the GJ channel contains fast and slow gates that are sensitive to transjunctional voltage (Vj). We developed a stochastic 16-state model (S16SM) that details the operation of two fast and two slow gates(More)
A well-known example of global optimization that provides solutions within fixed error limits is optimization of functions with a known Lipschitz constant. In many real-life problems this constant is unknown. To address that, we propose a novel method called Pareto–Lipschitzian Optimization (PLO) that provides solutions within fixed error limits for(More)
A simple Stock Exchange Game Model (SEGM) was introduced in Mockus (2003), to simulate the behavior of several stockholders using fixed buying-selling margins at fixed bank yield. In this paper, an extended model USEGM is proposed. The advantage of USEGM is application of the Nash Equilibrium (NE) to strategies that define buying-selling margins and bank(More)