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- W2090395152 abstract "Conventional methods of solving nonconvex separable programming (NSP) problems by mixed integer programming methods requires adding numerous 0–1 variables. In this work, we present a new method of deriving the global optimum of a NSP program using less number of 0–1 variables. A separable function is initially expressed by a piecewise linear function with summation of absolute terms. Linearizing these absolute terms allows us to convert a NSP problem into a linearly mixed 0–1 program solvable for reaching a solution which is extremely close to the global optimum." @default.
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- W2090395152 title "A global optimization method for nonconvex separable programming problems" @default.
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- W2090395152 doi "https://doi.org/10.1016/s0377-2217(98)00243-4" @default.
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