Asim K. Das

A. K. Ojha, A. K. Das

Geometric programming problems occur frequently in engineering design and management. In multiobjective optimization, the trade-off information between different objective functions is probably the most important piece of information in a solution process to reach the most preferred solution. In this paper we have discussed the basic concepts and principles of multiple objective optimization problems and developed a solution procedure to solve this optimization problem where the cost coefficients are continuous functions using weighted method to obtain the non-inferior solutions.

A. K. Ojha, A. K. Das

Geometric programming (GP) provides a power tool for solving a variety of optimization problems. In the real world, many applications of geometric programming (GP) are engineering design problems in which some of the problem parameters are estimating of actual values. This paper develops a solution procedure to solve nonlinear programming problems using GP technique by splitting the cost coefficients, constraint coefficients and exponents with the help of binary numbers. The equivalent mathematical programming problems are formulated to find their corresponding value of the objective function based on the duality theorem. The ability of calculating the cost coefficients, constraint coefficients and exponents developed in this paper might help lead to more realistic modeling efforts in engineering design areas. Standard nonlinear programming software has been used to solve the proposed optimization problem. Two numerical examples are presented to illustrate the method.