Abstract

In the past decade, increasing interest in equity issues resulted in new methodologies in the area of operations research. This paper deals with the concept of equitably efficient solutions to multiple criteria optimization problems. Multiple criteria optimization usually starts with an assumption that the criteria are incomparable. However, many applications arise from situations which present equitable criteria. Moreover, some aggregations of criteria are often applied to select efficient solutions in multiple criteria analysis. The latter enforces comparability of criteria (possibly rescaled). This paper presents aggregations which can be used to derive equitably efficient solutions to both linear and nonlinear multiple optimization problems. An example with equitable solutions to a capital budgeting problem is analyzed in detail. An equitable form of the reference point method is introduced and analyzed.

Abstract

Globally observed trends in aging indicate that older adults constitute a growing share of the population and an increasing demographic in the modern technologies marketplace. Therefore, it has become important to address the issue of participation of older adults in the process of developing solutions suitable for their group. In this study, we approached this topic by organizing a hackathon involving teams of young programmers and older adults participants. Below we describe a case study of that hackathon, in which our objective was to motivate older adults to participate in software engineering processes. Based on our results from an array of qualitative methods, we propose a set of good practices that may lead to improved older adult participation in similar events and an improved process of developing apps that target older adults.

In systems which serve many users there is a need to respect some fairness rules while looking for the overall efficiency. This applies among others to network design where a central issue is how to allocate bandwidth to flows efficiently and fairly. The so-called max-min fairness is widely used to meet these goals. However, allocating the bandwidth to optimize the worst performance may cause a large worsening of the overall throughput of the network. In this paper we show how the concepts of mult-criteria equitable optimization can effectively be used to generate various fair and efficient allocation schemes. We introduce a multi-criteria model equivalent to equitable optimization and we develop a corresponding reference point procedure to generate fair and efficient bandwidth allocations. Our analysis is focused on the nominal network design for elastic traffic that is currently the most significant traffic of IP networks. The procedure is tested on a sample network dimensioning problem for elastic traffic and its abilities to model various preferences are demonstrated. ᭧