A fuzzy multicriteria benefit-cost approach for irrigation projects evaluation

Three alternative irrigation projects for the East Macedonia-Thrace Region, Greece, are considered. Given the presence of valuable natural ecosystems in the area, environmental considerations are of great importance. In order to evaluate the projects, a fuzzy multicriteria benefit-cost approach is proposed. The overall goal is the rational management of water resources, and the projects appraisal is based on economic, social, and environmental criteria. Alternative scenarios on the availability of water resources are also incorporated in the decision model. The decision problem is formulated as two hierarchies, and the projects are ranked according to the benefit-cost ratio of their global priorities. The proposed method is proved to be, on the one hand, very suitable when both costs and benefits cannot be easily expressed into monetary terms as the traditional benefit-cost analysis requires; and, on the other hand, a valuable tool to cope with vague judgments.Analytic hierarchy process Decision making Fuzzy sets Linguistic variables Water resources planning

A reactive greedy randomized adaptive search procedure for a mixed integer portfolio optimization problem

Purpose – The purpose of this paper is to present a procedure for finding the efficient frontier, i.e. a non-decreasing curve representing the set of Pareto-optimal or non-dominated portfolios, when the standard Markowitz' classical mean-variance model is enriched with additional constraints. Design/methodology/approach – The mean-variance portfolio optimization model is extended to include integer constraints that limit a portfolio to have a specified number of assets, and to impose limits on the proportion of the portfolio held in a given asset. Optimization-based procedures run into difficulties in this framework and this motivates the investigation of heuristic algorithms to find acceptable solutions. Findings – The problem is solved by a greedy randomized adaptive search procedure (GRASP), enhanced by a learning mechanism and a bias function for determining the next element to be introduced in the solution. Originality/value – This is believed to be the first time, a GRASP for finding the efficient frontier for this class of portfolio selection problems is used.Modelling, Optimization techniques, Portfolio investment

Application of Evolutionary Algorithms in Project Management

Part 7: Genetic AlgorithmsInternational audienceThe paper deals with “resource leveling optimization problems”, a class of problems that are often met in modern project management. The problems of this kind refer to the optimal handling of available resources in a candidate project and have emerged, as the result of the even increasing needs of project managers in facing project complexity, controlling related budgeting and finances and managing the construction production line. For the effective resource leveling optimization in problem analysis, evolutionary intelligent methodologies are proposed. Traditional approaches, such as exhaustive or greedy search methodologies, often fail to provide near-optimum solutions in a short amount of time, whereas the proposed intelligent approaches manage to quickly reach high quality near-optimal solutions. In this paper, a new genetic algorithm is proposed for the investigation of the start time of the non-critical activities of a project, in order to optimally allocate its resources. Experiments with small and medium size benchmark problems taken from publicly available project data resources, produce highly accurate resource profiles. The proposed methodology proves capable of coping with larger size project management problems, where conventional techniques like complete enumeration is impossible, obtaining near-optimal solutions