A prescriptive approach to qualify and quantify customer value for value-based requirements engineering

Recently, customer-based product development is becoming a popular paradigm. Customer expectations and needs can be identified and transformed into requirements for product design with the help of various methods and tools. However, in many cases, these models fail to focus on the perceived value that is crucial when customers make the decision of purchasing a product. In this paper, a prescriptive approach to support value-based requirements engineering (RE) is proposed, describing the foundations, procedures and initial applications in the context of RE for commercial aircraft. An integrated set of techniques, such as means-ends analysis, part-whole analysis and multi-attribute utility theory is introduced in order to understand customer values in depth and width. Technically, this enables identifying the implicit value, structuring logically collected statements of customer expectations and performing value modelling and simulation. Additionally, it helps to put in place a system to measure customer satisfaction that is derived from the proposed approach. The approach offers significant potential to develop effective value creation strategies for the development of new product

A comparative study of multiple-criteria decision-making methods under stochastic inputs

This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative

A Methodology for Public-Planner Interaction in Multiobjective Project Planning and Evaluation

A review of current multiple objective planning techniques is presented. A critique of certain classes of these techniques is offered, especially in terms of the degree to which they facilitate certain information needs of the planning process. Various tools in operations research are used to constructed a new multiple objective planning methodology, called the Vector Optimization Decision Convergence Algorithm (VODCA). An application of the methodology pertaining to water resources development in Utah is documented

The Pareto Frontier for Random Mechanisms

We study the trade-offs between strategyproofness and other desiderata, such as efficiency or fairness, that often arise in the design of random ordinal mechanisms. We use approximate strategyproofness to define manipulability, a measure to quantify the incentive properties of non-strategyproof mechanisms, and we introduce the deficit, a measure to quantify the performance of mechanisms with respect to another desideratum. When this desideratum is incompatible with strategyproofness, mechanisms that trade off manipulability and deficit optimally form the Pareto frontier. Our main contribution is a structural characterization of this Pareto frontier, and we present algorithms that exploit this structure to compute it. To illustrate its shape, we apply our results for two different desiderata, namely Plurality and Veto scoring, in settings with 3 alternatives and up to 18 agents.Comment: Working Pape

Effective and efficient algorithm for multiobjective optimization of hydrologic models

Practical experience with the calibration of hydrologic models suggests that any single-objective function, no matter how carefully chosen, is often inadequate to properly measure all of the characteristics of the observed data deemed to be important. One strategy to circumvent this problem is to define several optimization criteria (objective functions) that measure different (complementary) aspects of the system behavior and to use multicriteria optimization to identify the set of nondominated, efficient, or Pareto optimal solutions. In this paper, we present an efficient and effective Markov Chain Monte Carlo sampler, entitled the Multiobjective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm, which is capable of solving the multiobjective optimization problem for hydrologic models. MOSCEM is an improvement over the Shuffled Complex Evolution Metropolis (SCEM-UA) global optimization algorithm, using the concept of Pareto dominance (rather than direct single-objective function evaluation) to evolve the initial population of points toward a set of solutions stemming from a stable distribution (Pareto set). The efficacy of the MOSCEM-UA algorithm is compared with the original MOCOM-UA algorithm for three hydrologic modeling case studies of increasing complexity

Requirement Analysis and Implementation of Multicriteria Analysis in the NEEDS Project

This report specifies the requirements for and implementation of the multicriteria analysis of future energy technologies performed by a large number of stakeholders within the EU-funded integrated projct NEEDS. The report is composed of two main parts and the appendix. The first part starts with a summary of the objectives of the analysis followed by a detailed specifiation of the analyzed problem, in particular the analysis context, discussion of the sets of criteria and alternatives, and the participation of the stakeholders. Next, the planned problem analysis process is first outlined, and then discussed in more detail. Finally, the requirements for the multicritria analysis are specified. The second part deals with the implementation of the dedicated Web-site developed for this analysis, and later extended to support analysis of any multicriteria choice between discrete alternatives. It starts with an overview of the problem analysis process and the corresponding basic assumptions. Te architecture of the application and its features are then presented. Lessons learned from the development and use of this application conclude this part of the report. The appendix contains a review of the state-of-the-art of applying multicriteria analysis to energy problems, as well as characteristics of three applications that exploit the multicriteria analysis methods for energy problems considered relevant to the analysis reported in this paper

A formal design synthesis and optimization method for systems architectures

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