Aspiration/reservation-based decision support—a step beyond goal programming

Real-life decision problems are usually so complex that they cannot be modelled with a single objective function, thus creating a need for clear and efficient techniques for handling multiple criteria to support the decision process. A widely used technique and one commonly taught in general OR/MS courses is goal programming, which is clear and appealing. On the other hand, goal programming is strongly criticized by multiple-criteria optimization specialists for its non-compliance with the efficiency (Pareto-optimality) principle. In this paper we show how the implementation techniques of goal programming can be used to model the reference point method and its extension, aspiration/reservation-based decision support. Thereby we show a congruence between these approaches and suggest how the GP model with relaxation of some traditional assumptions can be extended to an efficient decision support technique meeting the efficiency principle and other standards of multiobjective optimization theory.     

Price-directive decision making in hierarchical systems with conflicting preferences

In this paper we consider a classical model of price-directive decision making in hierarchical organizations, namely Dantzig-Wolfe decomposition, well known from single-objective programming. Here, however, we allow for preference differences that are usually observed between a central unit and a subunit in an organizational structure. The procedure models, therefore, how decision making may evolve in a context with decentralized information as well as intra- and interpersonal conflicts. Several numerical experiments with the procedure have been performed. The results of those experiments demonstrate that the procedure in many instances converges towards an efficient solution, despite the differences in the criteria weights used in the master problem and the subproblem respectively. This suggests that some amount of goal discordance need not prohibit efficient decision making in a hierarchical organization.     

Using logic programming for theory representation and scientific inference

The aim of this paper is to show that logic programming is a powerful tool for representing scientific theories and for scientific inference. In a logic program it is possible to encode the qualitative and quantitative components of a theory in first order predicate logic, which is a highly expressive formal language. A theory program can then be handed to an algorithm that reasons about the theory. We discuss the advantages of logic programming with regard to building formal theories and present a novel software package for scientific inference: Theory Toolbox. Theory Toolbox can derive any conclusions that are entailed by a theory, explain why a certain conclusion follows from a theory, and evaluate a theory with regard to its internal coherence and generalizability. Because logic is, or should be, a cornerstone of scientific practice, we believe that our paper can make an important contribution to scientific psychology.     

ACADEA—a decision support system for faculty performance reviews

ACADEA, a multi‐criteria decision support system for the performance review of individual faculty, is presented. Developed from the point of view of a department that is facing exogenously as well as self imposed objectives, the support system looks upon the aggregate performance of an academic department as the result of individual faculty member's multi‐criteria evaluations. Five objectives, research output, teaching output, external service, internal service and cost, are operationalized into criteria. The system is applied to a university department with 30 faculty members evaluated over a 3‐year period. The results identify promotional candidates and reveal underlying problems in managerial consistency, departmental sub‐groupings and the incentive structure. The outcomes of the support system are consistent with the position that equity in faculty governance does not necessarily imply equal loads on all tasks. Copyright © 2000 John Wiley & Sons, Ltd.     

Examining implications of the developmental timing of maternal trauma for prenatal and newborn outcomes

Separate literatures have demonstrated that mothers’ experiences with trauma during childhood or pregnancy are associated with maternal prenatal health risks, adverse childbirth outcomes, and offspring internalizing and externalizing disorders. These literatures largely align with the intergenerational transmission or fetal programming frameworks, respectively. However, few studies have tested the effects of maternal childhood and prenatal trauma simultaneously on mothers’ and infants’ health outcomes, and no studies have examined these effects on newborn neurobehavioral outcomes. Thus, in the present study, we examined how the developmental timing of pregnant women’s traumatic life experiences associated with their physical health and psychopathology (Aim 1) as well as their newborns’ birth and neurodevelopmental outcomes (Aim 2; for pre-registered aims and hypotheses, see https://osf.io/ygnre/?view_only=cbe17d0ac7f24af5a4d3e37e24eebead). One hundred and fifty-two 3rd trimester pregnant women (M_age = 29 years; 17.1% Hispanic/Latina) completed measures of trauma history and psychopathology. Then, 24–48 h after birth, trained clinicians conducted newborn neurobehavioral exams (n = 118 newborns; 52.6% female). Results indicated that lifetime traumatic experiences associated with multiple prenatal maternal health outcomes, including depression, anxiety, emotion dysregulation, and pregnancy complications. Pregnant women’s experiences with childhood trauma, but not adulthood or prenatal trauma, predicted higher neurobehavioral attention scores among female newborns. Our discussion highlights the importance of considering the developmental timing of maternal trauma on perinatal outcomes and contextualizes our findings within the intergenerational transmission and fetal programming literatures.Data AvailabilityData pertaining to R01MH119070 (MPIs Crowell & Conradt) and that support these findings are uploaded to the NIMH repository.     

Model and interactive algorithm of bi‐level multi‐objective decision‐making with multiple interconnected decision makers

Furthering a prior research on two‐person bi‐level multi‐objective decision‐making problems of the leader‐follower Stackelberg game, we present an extended model of bi‐level multi‐objective decision‐making with multiple interconnected decision makers at the lower level. In the model, the upper level decision maker acts as a leader and the lower level decision makers behave as the followers, and inter‐connections and interactions exist among these followers in decision‐making scenarios. Following the rules of leader‐follower Stackelberg game, we develop an interactive algorithm of the model for solving multi‐objective decision‐making problems and reflecting the interactive natures among the decision makers. Finally, the authors exemplify the model and algorithm, and draw a conclusion on points of contributions and the significance of this study in decision‐making and support. Copyright © 2001 John Wiley & Sons, Ltd.     

Multiple objective programming with piecewise linear functions

An approach to generating all efficient solutions for multiple objective programs with piecewise linear objective functions and linear constraints is presented. The approach is based on the decomposition of the feasible set into subsets, referred to as cells, so that the original problem reduces to a series of single objective linear programs and feasibility tests over the cells. The concepts of cell-efficiency and complex-efficiency are introduced and their relationship with efficiency is examined. A generic algorithm for finding efficient solutions for bi-objective piecewise linear programs is proposed. Applications in location theory as well as in worst case analysis are highlighted. Copyright © 1999 John Wiley & Sons, Ltd.     

Analytical Hierarchy Process Based Assignment Model for Allotting Parking Slots to Different Localities

Because of growing population and a consequent increase in number of vehicles, the problem of parking personal vehicles is becoming explosive. This paper suggests efficient use of surplus space to be utilized as parking slot using analytical hierarchy process and integer programming model. Examples covering a real situation justify the approach. Copyright © 2011 John Wiley & Sons, Ltd.