Simplified models for multi-criteria decision analysis under uncertainty

Includes abstract.Includes bibliographical references.When facilitating decisions in which some performance evaluations are uncertain, a decision must be taken about how this uncertainty is to be modelled. This involves, in part, choosing an uncertainty format {a way of representing the possible outcomes that may occur. It seems reasonable to suggest {and is an aim of the thesis to show {that the choice of how uncertain quantities are represented will exert some influence over the decision-making process and the final decision taken. Many models exist for multi-criteria decision analysis (MCDA) under conditions of uncertainty; perhaps the most well-known are those based on multi-attribute utility theory [MAUT, e.g. 147], which uses probability distributions to represent uncertainty. The great strength of MAUT is its axiomatic foundation, but even in its simplest form its practical implementation is formidable, and although there are several practical applications of MAUT reported in the literature [e.g. 39, 270] the number is small relative to its theoretical standing. Practical applications often use simpler decision models to aid decision making under uncertainty, based on uncertainty formats that `simplify' the full probability distributions (e.g. using expected values, variances, quantiles, etc). The aim of this thesis is to identify decision models associated with these `simplified' uncertainty formats and to evaluate the potential usefulness of these models as decision aids for problems involving uncertainty. It is hoped that doing so provides some guidance to practitioners about the types of models that may be used for uncertain decision making. The performance of simplified models is evaluated using three distinct methodological approaches {computer simulation, `laboratory' choice experiments, and real-world applications of decision analysis {in the hope of providing an integrated assessment. Chapter 3 generates a number of hypothetical decision problems by simulation, and within each problem simulates the hypothetical application of MAUT and various simplified decision models. The findings allow one to assess how the simplification of MAUT models might impact results, but do not provide any general conclusions because they are based on hypothetical decision problems and cannot evaluate practical issues like ease-of-use or the ability to generate insight that are critical to good decision aid. Chapter 4 addresses some of these limitations by reporting an experimental study consisting of choice tasks presented to numerate but unfacilitated participants. Tasks involved subjects selecting one from a set of five alternatives with uncertain attribute evaluations, with the format used to represent uncertainty and the number of objectives for the choice varied as part of the experimental design. The study is limited by the focus on descriptive rather than real prescriptive decision making, but has implications for prescriptive decision making practice in that natural tendencies are identified which may need to be overcome in the course of a prescriptive analysis

The treatment of uncertainty in multicriteria decision making

Bibliography: leaves 142-149.The nature of human decision making dictates that a decision must often be considered under conditions of uncertainty. Decisions may be influenced by uncertain future events, doubts regarding the precision of inputs, doubts as to what the decision maker considers important, and many other forms of uncertainty. The multicriteria decision models that are designed to facilitate and aid decision making must therefore consider these uncertainties if they are to be effective. In this thesis, we consider the treatment of uncertainty in multicriteria decision making (MCDM), with a specific view to investigating the types of uncertainty that are most relevant to MCDM, [and] how the uncertainties identified as relevant may be treated by various different MCDM methodologies

Behavioural analytics: Exploring judgments and choices in large data sets

The ever-increasing availability of large data-sets that store users’ judgements (such as forecasts and preferences) and choices (such as acquisitions of goods and services) provides a fertile ground for Behavioural Operational Research (BOR). In this paper, we review the streams of Behavioural Decision Research that might be useful for BOR researchers and practitioners to analyse such behavioural data-sets. We then suggest ways that concepts from these streams can be employed in exploring behavioural data-sets for (i) detecting behavioural patterns, (ii) exploiting behavioural findings and (iii) improving judgements and decisions of consumers and citizens. We also illustrate how this taxonomy for behavioural analytics might be utilised in practice, in three real-world studies with behavioural data-sets generated by websites and online user activity

Changes in the movement and calling behavior of minke whales (Balaenoptera acutorostrata) in response to navy training

This research was funded by the U.S. Office of Naval Research under grant number N000141612859. The passive acoustic data were recorded under support by COMPACFLT for the Navy Marine Species Monitoring Program. The call association tracking algorithm was developed under a separate U.S. Office of Naval Research project (2011–2015 Advanced Detection, Classification and Localization, grant number: N0001414IP20037).Many marine mammals rely on sound for foraging, maintaining group cohesion, navigation, finding mates, and avoiding predators. These behaviors are potentially disrupted by anthropogenic noise. Behavioral responses to sonar have been observed in a number of baleen whale species but relatively little is known about the responses of minke whales (Balaenoptera acutorostrata). Previous analyses demonstrated a spatial redistribution of localizations derived from passive acoustic detections in response to sonar activity, but the lack of a mechanism for associating localizations prevented discriminating between movement and cessation of calling as possible explanations for this redistribution. Here we extend previous analyses by including an association mechanism, allowing us to differentiate between movement responses and calling responses, and to provide direct evidence of horizontal avoidance responses by individual minke whales to sonar during U.S. Navy training activities. We fitted hidden Markov models to 627 tracks that were reconstructed from 3 years of minke whale (B. acutorostrata) vocalizations recorded before, during, and after naval training events at the U.S. Navy's Pacific Missile Range Facility, Kauai, Hawaii. The fitted models were used to identify different movement behaviors and to investigate the effect of sonar activity on these behaviors. Movement was faster and more directed during sonar exposure than in baseline phases. The mean direction of movement differed during sonar exposure, and was consistent with movement away from sonar-producing ships. Animals were also more likely to cease calling during sonar. There was substantial individual variation in response. Our findings add large-sample support to previous demonstrations of horizontal avoidance responses by individual minke whales to sonar in controlled exposure experiments, and demonstrate the complex nature of behavioral responses to sonar activity: some, but not all, whales exhibited behavioral changes, which took the form of horizontal avoidance or ceasing to call.Publisher PDFPeer reviewe

Fast and frugal heuristics for portfolio decisions with positive project interactions

Funding: ID is supported in part by funding from the National Research Foundation of South Africa (Grant ID 90782, 105782).We consider portfolio decision problems with positive interactions between projects. Exact solutions to this problem require that all interactions are assessed, requiring time, expertise and effort that may not always be available. We develop and test a number of fast and frugal heuristics – psychologically plausible models that limit the number of assessments to be made and combine these in computationally simple ways – for portfolio decisions. The proposed “add-the-best” family of heuristics constructs a portfolio by iteratively adding a project that is best in a greedy sense, with various definitions of “best”. We present analytical results showing that information savings achievable by heuristics can be considerable; a simulation experiment showing that portfolios selected by heuristics can be close to optimal under certain conditions; and a behavioral laboratory experiment demonstrating that choices are often consistent with the use of heuristics. Add-the-best heuristics combine descriptive plausibility with effort-accuracy trade-offs that make them potentially attractive for prescriptive use.PostprintPeer reviewe

Singing fin whale swimming behavior in the Central North Pacific

This research was supported by Commander, U.S. Pacific Fleet (Code N465JR, Award Number N0007020WR0EP8F), the Office of Naval Research (Code 322, Award Number N0001421WX00156), and tool development necessary for this analysis was supported by the U.S. Navy's Living Marine Resources Program (Award Number N0002520WR0141R).Male fin whales sing using 20 Hz pulses produced in regular patterns of inter-note intervals, but little is known about fin whale swimming behavior while they are singing. Even less is known about fin whales in Hawaiian waters because they have rarely been sighted during surveys and passive acoustic monitoring has been limited to sparse hydrophone systems that do not have localization capabilities. We hypothesized that fin whale kinematics may be related to their singing behavior, or external variables such as time and sea state. To investigate this hypothesis, we analyzed 115 tracks containing 50,034 unique notes generated from passive acoustic recordings on an array of 14 hydrophones from 2011 to 2017 at the U.S. Navy Pacific Missile Range Facility off Kauai, Hawaii. Fin whales swam at an average speed of 1.1 m/s over relatively direct paths. We incorporated the whales' speed and turning angle into hidden Markov models to identify different behavioral states based on the whales' movements. We found that fin whale kinematic behavioral state was related to the vocalization rate (also known as cue rate) and time of day. When cue rate was higher, fin whales were more likely to swim slower and turn more than when cue rate was lower. During the night, fin whales were also more likely to swim slower and turn more than during the day. In addition, we examined whether the presence of singing fin whales was related to time and sea state using generalized additive models. Fin whale track presence was affected by day of the year and song season, and possibly also wind speed and wave height. Although the track kinematics from the fin whale tracks presented here are limited to a subset of whales that are acoustically active, they provide some of the only detailed movements of fin whales in the region and can be compared against fin whale swim speeds in other regions. Understanding how fin whale swimming behavior varies based on their vocalization patterns, time, and environmental factors will help us to contextualize potential changes in whale behavior during Navy training and testing on the range.Publisher PDFPeer reviewe

North Pacific minke whales call rapidly when calling conspecifics are nearby

This research was supported by Commander, U.S. Pacific Fleet (Code N465JR, Award Number N0007020WR0EP8F) and tool development utilized for this analysis was supported by the U.S. Navy’s Living Marine Resources Program (Award Number N0002520WR0141R).North Pacific minke whale (Balaenoptera acutorostrata) boing calls are commonly detected in Hawaiian waters. When producing boing vocalizations, minke whales seem to be in one of two calling behavioral states. Most often minke whales produce boings with inter-call intervals of several minutes, but sometimes minke whales call rapidly with inter-call intervals of less than a minute. Since minke whales are difficult to detect visually, cue-rate-based density estimation using passive acoustic monitoring has been proposed. However, the variables that influence cue rate or calling rate are poorly understood in most whales, including minke whales. We collected passive acoustic recordings from 47 bottom-mounted hydrophones at the Pacific Missile Range Facility’s instrumented range off the coast of Kauaʻi, Hawaiʻi to test the hypothesis that minke whales call more rapidly when closer in proximity to other calling conspecifics. A total of 599 days of data were recorded between August 2012 and July 2017 and were automatically post-processed to detect, classify, and localize calls. Localized calls were grouped into tracks and manually validated, resulting in 509 individual tracks composed of 36,033 calls within a 16 x 39 km focal study area. Tracked minke whales exhibited a strong bimodal call rate with means of one call every 6.85 min (σ= 2.54 min) and 0.63 min (σ= 0.36 min). We ran hidden Markov models to quantify the relationship between call rate and the distance to the nearest calling conspecific. Overall, the probability of the higher call rate occurring increased as the distance to the nearest conspecific decreased, and the probability of the lower call rate occurring increased as the distance to the nearest conspecific increased. We also examined individual track data and found that minke whales may also exhibit other responses (i.e. increased speed, changes in heading, and cessation of calling) when calling conspecifics are nearby. These findings provide new information about minke whale calling behavior in what is likely a breeding area.Publisher PDFPeer reviewe

The Lombard effect in singing humpback whales : source levels increase as ambient ocean noise levels increase

Funding: Office of Naval Research (Code 322, Marine Mammals and Biology), Commander, U.S. Pacific Fleet (Code N465JR), and the Naval Facilities Engineering Command Living Marine Resources Program.Many animals increase the intensity of their vocalizations in increased noise. This response is known as the Lombard effect. While some previous studies about cetaceans report a 1 dB increase in the source level (SL) for every dB increase in the background noise level (NL), more recent data have not supported this compensation ability. The purpose of this study was to calculate the SLs of humpback whale song units recorded off Hawaii and test for a relationship between these SLs and background NLs. Opportunistic recordings during 2012-2017 were used to detect and track 524 humpback whale encounters comprised of 83 974 units on the U.S. Navy's Pacific Missile Range Facility hydrophones. Received levels were added to their estimated transmission losses to calculate SLs. Humpback whale song units had a median SL of 173 dB re 1 μ Pa at 1 m, and SLs increased by 0.53 dB/1 dB increase in background NLs. These changes occurred in real time on hourly and daily time scales. Increases in ambient noise could reduce male humpback whale communication space in the important breeding area off Hawaii. Since these vocalization changes may be dependent on location or behavioral state, more work is needed at other locations and with other species.Publisher PDFPeer reviewe

The use of the SMAA acceptability index in descriptive decision analysis

This paper proposes and evaluates a descriptive multiattribute choice model based upon the notion of acceptability developed in the stochastic multicriteria acceptability analysis (SMAA) methods. The acceptability index is simply the relative proportion of all possible preference structures that support the selection of a particular alternative, and is related to a model of choice in which attribute evaluations are relatively stable but what is desired changes as if at random. The model is tested using two longitudinal surveys of FMCG markets in Europe. The acceptability index is found to be positively associated with relative purchase frequencies at the individual and aggregate level, inversely related to defection rates, and positively related to changes in relative purchase frequencies over a six-month period.Choice theory Marketing Stochastic multicriteria acceptability analysis Consumer behaviour