An evolutionary approach to support decision making with linear decision models

In this paper we consider decision problems that can be described as linear decision models. These models have been traditionally solved using linear programming, fuzzy linear programming, multiple-objective linear programming or ‘what-if’ analysis. Using these approaches, one encounters a number of difficulties. We propose an ‘evolutionary approach’ to overcome these difficulties. In the proposed approach the decision maker does not have to precisely specify the model (i.e. the objective functions, the RHS values, etc.) at the beginning of the solution procedure. In fact, the model evolves as the solution procedure proceeds.     

Beneficence,Interests, and Wellbeing in Medicine: What It Means to Provide Benefit to Patients

Abstract

Beneficence is a foundational ethical principle in medicine. To provide benefit to a patient is to promote and protect the patient’s wellbeing, to promote the patient’s interests. But there are different conceptions of wellbeing, emphasizing different values. These conceptions of wellbeing are contrary to one another and give rise to dissimilar ideas of what it means to benefit a patient. This makes the concept of beneficence ambiguous: is a benefit related to the patient’s goals and wishes, or is it a matter of objective criteria that constitute wellbeing? This paper suggests a unified conception of wellbeing for use in medicine to determine what counts as a benefit. Two components of wellbeing are identified: (1) objective functioning/health and (2) the patient’s view of her own good. The paper explores how to apply, balance, and weigh these components in clinical situations to determine what counts as a benefit to a patient.