827,433 research outputs found

    The heterogeneous best-worst choice method in market research

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    WOS:000280441000009 (Nº de Acesso Web of Science)The article presents a market research technique for obtaining information on consumer preferences, called the heterogeneous best-worst (HBW) choice method. It accounts for preference heterogeneity, making it more accurate than the direct method (DM), and causes less information overload than other indirect methods. An example involving undergraduates picking a business school is presented to illustrate how the HBW choice method operates. It is demonstrated that the HBW and DM approaches produce very similar results, but the HBW method allows for more differentiation of extreme preferences

    Best-worst northern goshawk optimizer: a new stochastic optimization method

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    This study introduces a new metaheuristic method: the best-worst northern goshawk optimizer (BW-NGO). This algorithm is an enhanced version of the northern goshawk optimizer (NGO). Every BW-NGO iteration consists of four phases. First, each agent advances toward the best agent and away from the worst agent. Second, each agent moves relatively to the agent selected at random. Third, each agent conducts a local search. Fourth, each agent traces the space at random. The first three phases are mandatory, while the fourth phase is optional. Simulation is performed to assess the performance of BW-NGO. In this simulation, BW-NGO is confronted with four algorithms: particle swarm optimization (PSO), pelican optimization algorithm (POA), golden search optimizer (GSO), and northern goshawk optimizer (NGO). The result exhibits that BW-NGO discovers an acceptable solution for the 23 benchmark functions. BW-NGO is better than PSO, POA, GSO, and NGO in consecutively optimizing 22, 20, 15, and 11 functions. BW-NGO can discover the global optimal solution for three functions

    The STRESS Method for Boundary-point Performance Analysis of End-to-end Multicast Timer-Suppression Mechanisms

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    Evaluation of Internet protocols usually uses random scenarios or scenarios based on designers' intuition. Such approach may be useful for average-case analysis but does not cover boundary-point (worst or best-case) scenarios. To synthesize boundary-point scenarios a more systematic approach is needed.In this paper, we present a method for automatic synthesis of worst and best case scenarios for protocol boundary-point evaluation. Our method uses a fault-oriented test generation (FOTG) algorithm for searching the protocol and system state space to synthesize these scenarios. The algorithm is based on a global finite state machine (FSM) model. We extend the algorithm with timing semantics to handle end-to-end delays and address performance criteria. We introduce the notion of a virtual LAN to represent delays of the underlying multicast distribution tree. The algorithms used in our method utilize implicit backward search using branch and bound techniques and start from given target events. This aims to reduce the search complexity drastically. As a case study, we use our method to evaluate variants of the timer suppression mechanism, used in various multicast protocols, with respect to two performance criteria: overhead of response messages and response time. Simulation results for reliable multicast protocols show that our method provides a scalable way for synthesizing worst-case scenarios automatically. Results obtained using stress scenarios differ dramatically from those obtained through average-case analyses. We hope for our method to serve as a model for applying systematic scenario generation to other multicast protocols.Comment: 24 pages, 10 figures, IEEE/ACM Transactions on Networking (ToN) [To appear

    IMPLEMENTATION OF ANALYTICAL HIERARCHY PROCESS & BEST WORST METHOD IN SUPPLIER SELECTION

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    The incompatibility of the quality of the goods sent and the delay in delivery resulted in the company suffering losses and creating an unfavourable image in the company consumer's eyes. Both factors can be caused by error in the supplier selection process of raw material. The purpose of this research is to select the best supplier in the procurement process at the largest paper-producing company in Indonesia, which begins with determining the criteria that influence the selection of suppliers. The Analytical Hierarchy Process and the Best Worst Method were used in this study. Based on 4 personnel in the procurement department, 8 criteria were found for selecting suppliers with 3 alternative suppliers. The selected criteria are: Certificate Quality, Defect Rate, Offer Price, Discounts, Delivery Time, Order Fulfilment, Power Respond, and Work History. The offer price is the most important variable with a weight of 29.3%. Supplier A was selected with a score of 66.78%, while Supplier C became the second alternative priority and Supplier B became the third alternative priority

    Prioritizing quality dimensions for a Polymer industry using Best-Worst Method.

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    This research answers the complex decision-making question about identifying the quality dimensions in a polymer industry and to prioritize these quality dimensions to obtain the best quality product with minimum expenditure. This research takes use of expert opinion and right decision-making model to yield an optimal solution which will help the manufacturing plants to reduce wastage and to get a better consistent quality product throughout the production process

    Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques

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    Stated preference elicitation techniques, such as discrete choice experiments and best-worst scaling, are now widely used in health research to explore the public’s choices and preferences. In this paper, we propose an alternative stated preference elicitation technique, which we refer to as ‘trio-wise’. We explain this new technique, its relative advantages, modeling framework, and how it compares to the best-worst scaling method. To better illustrate the differences and similarities, we utilize best-worst scaling Case2, where individuals make best and worst (most and least) choices for the attribute levels that describe a single profile. We demonstrate this new preference elicitation technique using an empirical case study that explores preferences among the general public for ways to involve them in decisions concerning the health care system. Our findings show that the best-worst scaling and trio-wise preference elicitation techniques both retrieve similar preferences. However, the capability of our trio-wise method to provide additional information on the strength of rank preferences and its ability to accommodate indifferent preferences lead us to prefer it over the standard best-worst scaling technique

    Delay test for diagnosis of power switches

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    Power switches are used as part of power-gating technique to reduce leakage power of a design. To the best of our knowledge, this is the first work in open-literature to show a systematic diagnosis method for accurately diagnosingpower switches. The proposed diagnosis method utilizes recently proposed DFT solution for efficient testing of power switches in the presence of PVT variation. It divides power switches into segments such that any faulty power switch is detectable thereby achieving high diagnosis accuracy. The proposed diagnosis method has been validated through SPICE simulation using a number of ISCAS benchmarks synthesized with a 90-nm gate library. Simulation results show that when considering the influence of process variation, the worst case loss of accuracy is less than 4.5%; and the worst case loss of accuracy is less than 12% when considering VT (Voltage and Temperature) variations
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