Decisional Conflict and User Acceptance of Multicriteria Decision-Making Aids *

Despite the development of increasingly sophisticated and refined multicriteria decision-making (MCDM) methods, an examination of the experimental evidence indicates that users most often prefer relatively unsophisticated methods. In this paper, we synthesize theories and empirical findings from the psychology of judgment and choice to provide a new theoretical explanation for such user preferences. Our argument centers on the assertion that the MCDM method preferred by decision makers is a function of the degree to which the method tends to introduce decisional conflict. The model we develop relates response mode, decision strategy, and the salience of decisional conflict to user preferences among decision aids. We then show that the model is consistent with empirical results in MCDM studies. Next, the role of decisional conflict in problem formulation aids is briefly discussed. Finally, we outline future research needed to thoroughly test the theoretical mechanisms we have proposed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73461/1/j.1540-5915.1991.tb00371.x.pd

Nonlinear Integer Programming

Research efforts of the past fifty years have led to a development of linear integer programming as a mature discipline of mathematical optimization. Such a level of maturity has not been reached when one considers nonlinear systems subject to integrality requirements for the variables. This chapter is dedicated to this topic. The primary goal is a study of a simple version of general nonlinear integer problems, where all constraints are still linear. Our focus is on the computational complexity of the problem, which varies significantly with the type of nonlinear objective function in combination with the underlying combinatorial structure. Numerous boundary cases of complexity emerge, which sometimes surprisingly lead even to polynomial time algorithms. We also cover recent successful approaches for more general classes of problems. Though no positive theoretical efficiency results are available, nor are they likely to ever be available, these seem to be the currently most successful and interesting approaches for solving practical problems. It is our belief that the study of algorithms motivated by theoretical considerations and those motivated by our desire to solve practical instances should and do inform one another. So it is with this viewpoint that we present the subject, and it is in this direction that we hope to spark further research.Comment: 57 pages. To appear in: M. J\"unger, T. Liebling, D. Naddef, G. Nemhauser, W. Pulleyblank, G. Reinelt, G. Rinaldi, and L. Wolsey (eds.), 50 Years of Integer Programming 1958--2008: The Early Years and State-of-the-Art Surveys, Springer-Verlag, 2009, ISBN 354068274

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

A Reverse Logistics Network Model for Handling Returned Products

58827Due to the emergence of e-commerce and the proliferation of liberal return policies, product returns have become daily routines for many companies. Considering the significant impact of product returns on the company’s bottom line, a growing number of companies have attempted to streamline the reverse logistics process. Products are usually returned to initial collection points (ICPs) in small quantities and thus increase the unit shipping cost due to lack of freight discount opportunities. One way to address this issue is to aggregate the returned products into a larger shipment. However, such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to minimize the total cost by determining the optimal location and collection period of holding time of ICPs; determining the optimal location of a centralized return centre; transforming the nonlinear objective function of the proposed model formulation by Min et al. (2006a) into a linear form; and conducting a sensitivity analysis to the model solutions according to varying parameters such as shipping volume. Existing models and solution procedures are too complicated to solve real-world problems. Through a series of computational experiments, we discovered that the linearization model obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models.S

Exposure to fluctuating salinity enhances free amino acid accumulation in Tigriopus californicus (Copepoda)

Intracellular concentrations of free amino acids (FAA) in the intertidal copepod Tigriopus californicus increase in response to hyperosmotic stress and decrease in response to hypo-osmotic stress. The purpose of this study was to determine if exposure to repeated bouts of osmotic stress resulted in changes in FAA accumulation or the degree of FAA retention in subsequent episodes. Five groups of T. californicus were exposed for 22 days to a fluctuating salinity regime which consisted of 24 h at 100% seawater followed by 24 h at either 90, 80, 70, 60 or 50% seawater (11 cycles). After the tenth exposure to 100% seawater, individuals from each treatment group were analyzed for alanine and proline concentration. Alanine and proline accumulation generally increased in proportion to the osmotic stress up to 60–100% seawater — additional osmotic stress failed to increase total accumulation. Prior exposure to fluctuating salinity increased the extent of alanine and proline retention observed upon transfer to a hypo-osmotic medium. The treatment group which had experienced the most extreme fluctuation (50–100% seawater) retained alanine and proline levels approximately 10- and 20-fold higher, respectively, than controls. A less severe salinity fluctuation was required to elicit this response for alanine (90–100% seawater) than for proline (60–100% seawater). Previous exposure to fluctuating salinity also resulted in increased alanine and proline accumulation in subsequent episodes of hyperosmotic stress. 24 h after transfer from 50 to 100% seawater, alanine and proline levels in the conditioned copepods were approximately 3- and 7-fold higher, respectively, than in copepods which had not been cycled. This facilitation in alanine and proline accumulation occurred after 10 and 11 cycles, respectively. Of the increased accumulation in alanine and proline, 7.0% and 22.5%, respectively, could be accounted for by the higher degree of FAA retention while under hypo-osmotic conditions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47130/1/360_2004_Article_BF00692733.pd