In this paper, the need for rapid, low-cost changes in a design, in response to changes in performance requirements (PRs), within multi-objective problems, is considered. In the current study, the rapid response is attained through a priori design of a set of satisfying solutions, such that any PR may be satisfied by at least one member of the set. The purpose is to design such a set so that once the PRs change, the changes needed in order to adapt to the existing product (one member of the set) to the new requirements are minimal, while maintaining the aspiration for optimal performances. It is assumed here that minimal changes are related to small changes in the design parameters. In order to find the optimal set, sets of candidate solutions are evolved using an evolutionary multi-objective optimisation algorithm. The algorithm enhances a search pressure towards sets with minimal distances between their members (in design space) and with optimal performances, which are assessed by utilising the hyper-volume measure. An artificial and a real life example are utilised in order to explain the approach and to show its applicability to engineering problems.