Abstract
Abstract This paper presents further theoretical analysis and developments of entropy-based methods for mathematical programming. A new generalized multiplier function is given which approximates uniformly the maximum function, and from which the aggregate function is derived in a different way. Some new methods for minimax and constrained nonlinear programming problems are proposed. The convergence properties for these methods are discussed.
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