Multiobjective optimization (moo) in privatization

<title>Abstract</title> Deregulation of public enterprises and services by privatization is very fashionable nowadays. The aim of privatization is mainly to increase effectiveness, while the government itself likes to maximize its revenue at the occasion of the takeover. Most of these public enterprises show a shortage in investment while maintenance of a reasonable employment level in the new private firm is also strongly desirable, not to mention the ecological obligations imposed on the new private firm. It means that takeover bids have to face multiple objectives and different stakeholders, i.e., all the parties interested in the issue. Traditionally the optimization of all these objectives is then judged upon in a rather subjective way. Consequently, there is a need for a more general and objective, not to say scientific, method which can compare several takeover bids for privatization optimizing multiple objectives sometimes with different units of measurement. With that purpose, a method is developed, which takes into consideration upper limits, lower bounds, dominating and nondominating effects, ending up with a set of nondominated takeover bids, which are ranked by using ratio analysis and Reference Point Theory, whereas objectivity and decreasing marginal utility are fully respected [1]. A simulation on several takeover bids for a public enterprise given multiple objectives follows the theoretical explanation.