Two approaches to formal multiple objective decision analysis are described , illustrated and compared. These two approaches, generating techniques and goal programming, are illustrated by the solution of a simple numerical example. This solution combined with some lessons from the field of psychology provide a basis for some judgments on the relative merits of the approaches.

In many cases it is under legislative mandate to manage publicly owned forest resources for multiple uses (i.e., timber production, hunting, grazing). Forest resources have some particular characteristics which make rather difficult their management. In fact they are a typical example of a joint production (market and social goods) and therefore every management policy must face tradeoffs betwe...

Multiple-objective programming was used to examine the effects various objectives had on the optimal portfolio of sires chosen for a given breeding problem in a Jersey cow dairy herd. It was assumed that the dairy producer had the following three objectives in the breeding decision: to maximize Net Merit, to minimize inbreeding, and to minimize total expenditure on semen. Integer programming mo...

In this paper, a Goal Programming (GP) model is converted into a multi-objective optimization problem (MOO) of minimizing deviations from fixed goals. To solve the resulting MOO problem, a hybrid metaheuristic with two steps is proposed to find the Pareto set’s solutions. First, a Record-to-Record Travel with an adaptive memory is used to find first non-dominated Pareto frontier solutions preem...

Multiple Objective Programming (MOP) problems have become famous among many researchers due to more practical and realistic implementations. There have been a lot of methods proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP problems by starting from a utopian point (which is usually infeasible) and moving towards the...

In this paper relationships between Pareto points and saddle points in multiple objective programming are investigated. Convex and nonconvex problems are considered and the equivalence between Pareto points and saddle points is proved in both cases. The results are based on scalarizations of multiple objective programs and related linear and augmented Lagrangian functions. Partitions of the ind...

i This paper describes a solution technique mr Linear Programming problems with multiple objective functions. In this type of problem it is often necessary to replace the concept of "optimgm" with that of "best compromise". In contrast with methods dealing with a priori weighted sums of the objective functions, the method described here involves a sequential exploration of solutions. This explo...

It is a common characteristic of many multiple objective programming problems that the efficient solution set can only be identified in approximation: since this set often contains an infinite number of points, only a discrete representation can be computed, and due to numerical difficulties, each of these points itself might in general be only approximate to some efficient point. From among th...

Personal financial planning involves managing all the money activities during a planner’s lifetime. Traditional personal financial planning procedures begin with the planner’s financial status, goals, and expectations for the future before future cash flows of different time periods under various scenarios can be determined. If the planning results fail to meet the planner’s expectation, the pl...