AbstractThe sequential linear programming (SLP) method is one of the easiest optimization techniques used to treat non‐linear optimization problems. The successful application of the method is based on the proper choice of the move limits, which are unfortunately uncertain in the SLP algorithm. To enhance the efficiency and reliability of the SLP algorithm, six methods are proposed to calculate the move limits. The first three methods use the constraint equations to compute the minimum variations needed from the current design point to reach the constraint boundaries. The fourth method incorporates the cost function information as well as the constraints to figure out the move limits. The last two methods form a quadratic programming (QP) subproblem and solve for the change of the quadratic cost function. The move limits used in SLP are then computed from the estimated change of the linear cost function from the QP solution. Four numerical examples are employed to demonstrate the solution process by the methods proposed. The advantages and disadvantages of these methods are discussed.