A vague-set-based fuzzy multi-objective decision making model for bidding purchase

A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bid- ding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan’s supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of sat- isfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valua- tions for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs’ arbitrariness and subjectivity when these values are determined.

Kind of Fuzzy Method Determining Index Weight on Multi-Objctive Decision Making

Based on fuzzy characteristic of dicision-making thought, matrix of priority relation has been introduced and blurrized. A kind of fuzzy method, which is to determine the index weight on multi-objective decision making, has been put forward by means of the sequence root method for analysis of hierarchical process (AHP). Using this method an example which is to define the index weigbt on multi-objective decision making in thc scheme optimization of mine design has been given.

Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective decision making

Selective laser melting(SLM)is a unique additive manufacturing(AM)category that can be used to manufacture mechanical parts.It has been widely used in aerospace and automotive using metal or alloy powder.The build orientation is crucial in AM because it affects the as-built part,including its part accuracy,surface roughness,support structure,and build time and cost.A mechanical part is usually composed of multiple surface features.The surface features carry the production and design knowledge,which can be utilized in SLM fabrication.This study proposes a method to determine the build orientation of multi-feature mechanical parts(MFMPs)in SLM.First,the surface features of an MFMP are recognized and grouped for formulating the particular optimization objectives.Second,the estimation models of involved optimization objectives are established,and a set of alternative build orientations(ABOs)is further obtained by many-objective optimization.Lastly,a multi-objective decision making method integrated by the technique for order of preference by similarity to the ideal solution and cosine similarity measure is presented to select an optimal build orientation from those ABOs.The weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchy process.Two case studies are reported to validate the proposed method with numerical results,and the effectiveness comparison is presented.Physical manufacturing is conducted to prove the performance of the proposed method.The measured average sampling surface roughness of the most crucial feature of the bracket in the original orientation and the orientations obtained by the weighted sum model and the proposed method are 15.82,10.84,and 10.62μm,respectively.The numerical and physical validation results demonstrate that the proposed method is desirable to determine the build orientations of MFMPs with competitive results in SLM.

An Improved Interactively Method Based on Fuzzy Satisfying Degree for Multi-objective Decision Making

In order to make a decision in the face of multiple objectives, it is necessary to know the relative importance of the different objectives. Yet, it is often very difficult to specify a set of precise weights before possible alternatives solutions are known. In this paper, we present an improved weighted method, which is based on a modified definition by the membership function of fuzzy theory; an interactive, iterative method for arriving at an acceptable solution. The decision maker gradually discerns what is achievable and adjusts his aspirations and implicitly the specification of weights and trade-offs between his objectives, in the light of what he learns. To aid the decision maker＇s cognition and to allow him to express his wishes in a natural way, we present decision maker with grey relational degree to select the best solution from the finite solutions.

Human Centered Design in Multi-agent Virtual Environment

The efficient and reliable human centered design of products and processes is a major goal in manufacturing industries for numerous human factors must be taken into account during the entire life cycle of products. A multi-agents intelligent design system is presented for manufacturing process simulation and products＇ ergonomic analysis. In virtual design environment, the virtual human with high-level intelligence performs tasks＇ operation autonomously and shows optimum posture configuration with ergonomic assessment results in real time. The functions are realized by intelligent agents architecture based on a modem approach derived from fuzzy multi-objects decision-making theory. A case study is presented to demonstrate the feasibility of the suggested methodology.

BEST WEIGHT PATTERN EVALUATION BASED SECURITY CONSTRAINED POWER DISPATCH ALGORITHM

This paper presents a methodology which determines the allocation of power demand among the committed generating units while minimizes number of objectives as well as meets physical and technological system constraints. The procedure considers two decoupled problems based upon the dependency of their goals on either active power or reactive power generation. Both the problems have been solved sequentially to achieve optimal allocation of active and reactive power generation while minimizes operating cost, gaseous pollutants emission objectives and active power transmission loss with consideration of system operating constraints along with generators prohibited operating zones and transmission line flow limits. The active and reactive power line flows are obtained with the help of generalized generation shift distribution factors （GGDF） and generalized Z-bus distribution factors （GZBDF）, respectively. First problem is solved in multi-objective framework in which the best weights assigned to objectives are determined while employing weighting method and in second problem, active power loss of the system is minimized subject to system constraints. The validity of the proposed method is demonstrated on 30-bus IEEE power system.