Supplier Portfolio Selection and Optimum Volume Allocation: A Knowledge Based Method

Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case study that was conducted within the logistics unit of Shell Chemicals Europe. The proposed method is based on the classical view by Sprague and Carlson of sequence and interaction of the different phases of decision making in a decision support system and supports Kraljic’s portfolio approach for supplier management. This method aims to help the managers in making decisions on the allocation of volumes to suppliers while simultaneously trying to satisfy conflicting objectives of improvement in benefit and reduction in risk. A mathematical model to struc-ture the problem is presented, knowledge elicited from the managers is used to parameterize the mathemati-cal model and a multi-objective, hierarchical optimization procedure produces ‘trade-off’ outputs. The man-agers can also conduct interactive post optimization ‘what-if’ analysi

A decision-making methodology for selecting trigeneration systems

The paper considers the selection of a cogeneration system as a multicriteria decision-making problem, which involves economical, technical, thermodynamic and environmental issues. Taking into account the preference information given by the Decision-Maker (DM) about the weight of each criterion, a ranked set of alternatives is obtained by solving a discrete optimization problem based on the Tchebycheff metric. The problem definition, the structure and the solution algorithms are described. The DM can identify the most favorable alternatives in a finite number of steps. The method is illustrated with the help of an example

A systematic approach to design for lifelong aircraft evolution

Modern aerospace systems rely heavily on legacy platforms and their derivatives. Historical examples show that after a vehicle design is frozen and delivered to a customer, successive upgrades are often made to fulfill changing requirements. Current practices of adapting to emerging needs with derivative designs, retrofits, and upgrades are often reactive and ad-hoc, resulting in performance and cost penalties. Recent DoD acquisition policies have addressed this problem by establishing a general paradigm for design for lifelong evolution. However, there is a need for a unified, practical design approach that considers the lifetime evolution of an aircraft concept by incorporating future requirements and technologies. This research proposes a systematic approach with which the decision makers can evaluate the value and risk of a new aircraft development program, including potential derivative development opportunities. The proposed Evaluation of Lifelong Vehicle Evolution (EvoLVE) method is a two- or multi-stage representation of the aircraft design process that accommodates initial development phases as well as follow-on phases. One of the key elements of this method is the Stochastic Programming with Recourse (SPR) technique, which accounts for uncertainties associated with future requirements. The remedial approach of SPR in its two distinctive problem-solving steps is well suited to aircraft design problems where derivatives, retrofits, and upgrades have been used to fix designs that were once but no longer optimal. The solution approach of SPR is complemented by the Risk-Averse Strategy Selection (RASS) technique to gauge risk associated with vehicle evolution options. In the absence of a full description of the random space, a scenario-based approach captures the randomness with a few probable scenarios and reveals implications of different future events. Last, an interactive framework for decision-making support allows simultaneous navigation of the current and future design space with a greater degree of freedom. A cantilevered beam design problem was set up and solved using the SPR technique to showcase its application to an engineering design setting. The full EvoLVE method was conducted on a notional multi-role fighter based on the F/A-18 Hornet.Ph.D.Committee Chair: Mavris, Dimitri; Committee Member: Bishop, Carlee; Committee Member: Costello, Mark; Committee Member: Nam, Taewoo; Committee Member: Schrage, Danie

MULTIPLE-OBJECTIVE DECISION MAKING FOR AGROECOSYSTEM MANAGEMENT

Multiple-objective decision making (MODEM) provides an effective framework for integrated resource assessment of agroecosystems. Two elements of integrated assessment are discussed and illustrated: (1) adding noneconomic objectives as constraints in an optimization problem; and (2) evaluating tradeoffs among competing objectives using the efficiency frontier for objectives. These elements are illustrated for a crop farm and watershed in northern Missouri. An interactive, spatial decision support system (ISDSS) makes the MODEM framework accessible to unsophisticated users. A conceptual ISDSS is presented that assesses the socioeconomic, environmental, and ecological consequences of alternative management plans for reducing soil erosion and nonpoint source pollution in agroecosystems. A watershed decision support system based on the ISDSS is discussed.Agribusiness,

Sustainable urban development in practice:the SAVE concept

The need for sustainable development of the urban environment presents the research community with a number of challenges and opportunities. A considerable volume of research has been undertaken into the constituent parts of this complex problem and a number of tool kits and methodologies have been developed to enable and encourage the application of specific aspects of research in practice. However, there is limited evidence of the holistic integration of the body of knowledge arising from the research within real-life decision-making practices. In this paper we present an overview of the existing body of knowledge relating to sustainable development of the urban environment and propose a generic framework for its integration within current practices. This framework recognises the need to: understand social, economic, and environmental issues; understand the decision-making processes; provide a means of measurement, assessment, or valuation of the issues; provide analytical methods for the comparative assessment of complex data to enable an evaluation of strategies and design options and to communicate effectively throughout the process with a wide range of stakeholders. The components of a novel sustainability assessment, visualisation and enhancement (SAVE) framework, developed by the authors to ‘operationalise’ the body of knowledge are presented and justified. These include: decision-mapping methods to identify points of intervention; indicator identification and measurement approaches; appropriate mathematical and analytical tools and an interactive simulation and visualisation platform which integrates and communicates complex multivariate information to diverse stakeholder groups. We report on the application of the SAVE framework to a major urban development project and reflect on its current and potential impact on the development. Conclusions are also drawn about its general applicability

Multiobjective optimization as a decision aid for managing build-to-order supply chains

This paper provides an overview of multiobjective optimization (MOO) as a decision aid in build-to-order supply chains (BTO-SC). The main features of BTO-SCs are discussed along with capabilities of MOO to enhance decision making at different points along the chain. Key decision points across a typical BTO-SC are identified and potential applications of MOO are discussed. A sample application is presented and future avenues for further research highlighted