救捞工程中的多指标决策方法探讨

建立了基于综合权重的双基点多指标决策模型。分别从主观和客观两个方面来分析评估指标的权重,迭加得到综合权重,并利用它进行相对贴近度分析,从而判断方案的优劣,得到最佳方案,使问题的优化与决策更加科学、合理。以拖带方案的优化决策分析为例,验证了多指标决策模型的可行性,简述了它在救捞工程中的应用方法。     

A novel hybrid multiple criteria decision making model for material selection with target-based criteria

In engineering design, the decision to select an optimal material for a particular product is a problem requiring multi-criteria decision analysis that involves both qualitative and quantitative factors. The evaluation of alternative materials may be based on imprecise information or uncertain data. Furthermore, there can be significant dependence and feedbacks between the different criteria for material selection. However, most existing decision approaches cannot capture these complex interrelationships. In response, this paper proposes a general framework for evaluating and selecting the best material for a given application. A novel hybrid multiple criteria decision making (MCDM) model combining DEMATEL-based ANP (DANP) and modified VIKOR is used to solve the material selection problems of multiple dimensions and criteria that are interdependent. Moreover, target-based criteria as well as cost and benefit criteria can be addressed simultaneously in the proposed model. Finally, an empirical case concerning the bush material selection for a split journal bearing is presented to illustrate the potential of the new model. The results show that the proposed method for material selection is effective and provides meaningful implications for designers and engineers to refer.     

An application of multiple criteria decision making principles for planning machining operations

Some recently introduced concepts of multiple criteria decision making (MCDM), such as the range of compromise and its use in dimensionless weighting of the objectives, are employed to formulate machining recommendations under multiple machining criteria. Two approaches are presented and applied to the machining of 390 die cast aluminum alloy. The first is a graphical presentation of nondominated solutions from which an appropriate solution can be chosen under varying applications, requirements, and priorities. The second is the formulation of a composite function of the objectives through dimensionless weighting to select the optimum machining variables under given aspiration levels for the machining criteria.     

A multiple criteria decision making approach for the assembly line balancing problem

In practice, measuring total profit for a given assembly line balancing (ALB) problem is an involved process that is sometimes impossible because of much uncertainty and unavailability of data. In this paper, ALB is formulated as a multiple criteria problem where several easily quantifiable criteria (objectives) and constraints are defined. Objective functions include number of stations, cycle time, and operations cost, all to be minimized. After a discussion of applications and an overview of multiple criteria decision making (MCDM) approaches for ALB, the MCDM-ALB problem is formulated. Basic definitions and properties of MCDM for ALB are outlined and then an interactive MCDM approach is developed for solving the MCDM-ALB problem. To solve the problem, the decision maker (DM) interactively responds to paired comparisons of multicriteria alternatives. Through a limited number of interactions with the DM, the most preferred alternative is obtained. Many unexplored alternatives are eliminated by using a one-dimensional multiple criteria search. To present the DM's preference, we use the most flexible and general class of utility functions; namely, either quasi-concave or quasi-convex utility functions. An example is solved and computational experiments are reported. It is demonstrated that the bicriteria ALB, cycle time versus number of stations, can be easily solved by using the developed procedure. For the case that there are different criteria, an improved goal programming is developed to solve the MCDM-ALB problem. The motivation for development of the method, based on a case study of a lamp-making plant of the General Electric Company, is discussed.     

Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods

Nowadays machining of materials in their hardened state, also called hard machining, is a challenge in production of tools and molds. It has some advantages such as lower process time and lower manufacturing cost when compared to conventional machining. In machining of hard workpiece materials, however, very high stresses act on the tool holder through the cutting tool. These stresses necessitate the tool holder to have some specific properties. Especially in hard milling, the tool holder should have high stiffness and should be able to dissipate the energy generated during interrupted cutting. Material cost of the tool holder is also important since lower costs provide a competitive advantage for manufacturers. The material selection for the tool holder should be conducted considering aforementioned requirements. To tackle the difficulty of the material selection with specific properties from a large number of alternatives, multi-criteria decision-making (MCDM) methods have been used. In this paper a decision model including extended PROMETHEE II (EXPROM2) (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) methods were used for the selection of the best material for the tool holder used in hard milling. The criteria weighting was performed by compromised weighting method composed of AHP (analytic hierarchy process) and Entropy methods. The candidate materials were ranked by using these methods and the results obtained by each method were compared. It was confirmed that MCDM methods can be used for the solution of real time material selection problems. Tungsten carbide–cobalt and Fe–5Cr–Mo–V aircraft steel were found as the best materials for the tool holder production. The obtained results are found to be rather satisfactory and can be used in design stage of hard machining operations.     

Fuzzy multiple objective decision making approach to prioritize design requirements in quality function deployment

Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products to increase customer satisfaction by integrating marketing, design engineering, manufacturing, and other related functions of an organization. QFD focuses on delivering value by taking into account customer needs and then deploying this information throughout the development process. Although QFD aims to maximize customer satisfaction, technology and cost considerations limit the number and the extent of the possible design requirements that can be incorporated into a product. This paper presents a fuzzy multiple objective programming approach that incorporates imprecise and subjective information inherent in the QFD planning process to determine the level of fulfilment of design requirements. Linguistic variables are employed to represent the imprecise design information and the importance degree of each design objective. The fuzzy Delphi method is utilized to achieve the consensus of customers in determining the importance of customer needs. A pencil design example illustrates the application of the multiple objective decision analysis.     

Convergence to real-time decision making

Real-time decision making reflects the convergence of several digital technologies, including those concerned with the promulgation of artificial intelligence and other advanced technologies that underpin real-time actions. More specifically, real-time decision making can be depicted in terms of three converging dimensions: Internet of Things, decision making, and real-time. The Internet of Things include tangible goods, intangible services, ServGoods, and connected ServGoods. Decision making includes model-based analytics (since before 1990), information-based Big Data (since 1990), and training-based artificial intelligence (since 2000), and it is bolstered by the evolving real-time technologies of sensing (i.e., capturing streaming data), processing (i.e., applying real-time analytics), reacting (i.e., making decisions in real-time), and learning (i.e., employing deep neural networks). Real-time includes mobile networks, autonomous vehicles, and artificial general intelligence. Central to decision making, especially real-time decision making, is the ServGood concept, which the author introduced in an earlier paper (2012). It is a physical product or good encased by a services layer that renders the good more adaptable and smarter for a specific purpose or use. Addition of another communication sensors layer could further enhance its smartness and adaptiveness. Such connected ServGoods constitute a solid foundation for the advanced products of tomorrow which can further display their growing intelligence through real-time decisions.     

On the equivalence of operational performance measurement and multiple attribute decision making

Measurement of operational performance and decision making under multiple attributes are shown to be essentially the same process. A recent operational performance measurement (OPM) procedure called OCRA (operational competitiveness rating) and a multiple attribute decision making (MADM) method called TOPSIS (technique for order preference by similarity to ideal solution) are shown to produce ratings that are identical up to a linear transformation. Further investigations into OPM and MADM lead to their equivalence. The equivalence of the two methods can open up new research and application possibilities in both productivity analysis and MADM. Reviews of both the non-parametric approach that leads to the OC RA procedure and the TOPSIS method are provided, new perspectives on these methods are introduced and examples offered.     

Application of multi-criteria decision making methods for selection of micro-EDM process parameters

Ti-6Al-4V super alloy is an important engineering material with good strength to weight ratio and a wide range of applications in a number of engineering fields because of its excellent physical and mechanical properties.This work determines optimum process parameters such as pulse on time,peak current,gap voltage and flushing pressure,which influence the micro-electro discharge machining(EDM) process during machining of Ti-6A1-4V using combined methods of response surface methodology(RSM) and fuzzy-technique for order preference by similarity to ideal solution(TOPSIS).Central composite design(CCD) is used in the experimental investigation.A decision making model is developed to identify the optimum process parameters in the microEDM process,which influences several machining criterions such as material removal rate(MRR),tool wear rate(TWR),overcut(OC) and taper.Triangular fuzzy numbers are used to determine the weighting factor for each process criterion.Further a fuzzy-TOPSIS method is used to select the most desirable factor level combinations.The proposed technique can be used to select optimal process parameters from various sets of combinations of process parameters in a micro-EDM process.     

Material selection for thin-film solar cells using multiple attribute decision making approach

This paper presents a material selection approach for selecting absorbent layer material for thin-film solar cells (TFSCs) using multiple attribute decision making (MADM) approach. In this paper, different possible materials for absorbent layer and their properties like band gap, absorption coefficient, diffusion length, thermodynamic compatibility and recombination velocity is taken into consideration and MADM approach is applied to select the best material for thin-film solar cells. It is observed that Copper Indium Gallium Diselinide (CIGS) is the best material for the absorbent layer in thin-film solar cells out of all possible candidates. It was observed that the proposed result is in accordance with the experimental findings thus justifying the validity of the proposed study.     

Evaluating flexible manufacturing systems using a combined multiple attribute decision making method

This paper presents a logical procedure to evaluate alternative flexible manufacturing systems for a given industrial application. The procedure is based on a combined multiple attribute decision making method using TOPSIS and AHP methods together. A ‘flexible manufacturing system suitability index’ is proposed that evaluates and ranks flexible manufacturing systems for the given industrial application. The methodology is illustrated by means of an example.     

Optimization of process variables in drilling of carbon fiber reinforced plastics using various multi criteria decision making approaches

Carbon fiber-reinforced polymers are one of the lightweight materials used in structural design due to their exceptional mechanical performances. The drilling operation is indispensable as it facilitates the assembling of various manufactured components. However, drilling of fibrous laminates is deemed difficult in comparison to the traditional metals because of the anisotropic and non-homogeneous nature. The present work addresses the parametric effect on the drilled hole delamination and further reduces it with an optimal combination of parameters for multi-objectives using different multi-criterion decision-making techniques. Initially, the response surface-based regression model of delamination as a function of three static inputs has been developed, further revised with induced thrust as well as mean torque for the improvisation of the prediction capability. Finally, for the overall improvement, a decision-making model has been used that includes grey relation analysis, technique for order performance by similarity to ideal solution, and VIšekriterijumsko Kompromisno Rangiranje method. The delamination was found to be minimum at a low drill point angle (100°), high spindle rotation (2150 min⁻¹ ), and low feed rate (0.025 mm/rev) due to reduced thrust force. The mean absolute prediction error was significantly improved considering root mean square torque rather than axial thrust with process variables.     

Computer aided robot selection: the ‘multiple attribute decision making’ approach

This paper presents an efficient approach for a computer-based solution to the problem of selection of an ‘optimum robot’ specifically to aid industries. The approach breaks new ground by applying Multiple Attribute Decision Making (MADM) ideology to equipment selection (robots) which is of consequence because selection is an implicit aspect of design. Indeed, the approach is also applicable to a robot design problem. The robot selection procedure allows rapid convergence from a very large number to a manageable shortlist of potentially suitable robots using an ‘elimination search’ routine based on a few pertinent attributes of the robots. Subsequently, the selection procedure proceeds to rank the alternatives in the shortlist by employing a MADM method termed TOPS1S (Technique for Order Preference by Similarity to Ideal Solution). An expert system has been developed as part of the software package to assist an inexperienced user to establish priorities, and to ‘oversee’ the selection process at various stages. The procedure is also illustrated by an example.     

A subjective and objective integrated multiple attribute decision making method for material selection

The selection of an optimal material for an engineering design from among two or more alternative materials on the basis of two or more attributes is a multiple attribute decision making (MADM) problem. The selection decisions are complex, as material selection is more challenging today. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel MADM method for material selection for a considered design problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Three examples are presented to illustrate the potential of the proposed method.     

Managing uncertainty in multiple-criteria decision making related to sustainability assessment

In real life, decisions are usually made by comparing different options with respect to several, often conflicting criteria. This requires subjective judgements on the importance of different criteria by DMs and increases uncertainty in decision making. This article demonstrates how uncertainty can be handled in multi-criteria decision situations using Compromise Programming, one of the Multi-criteria Decision Analysis (MCDA) techniques. Uncertainty is characterised using a probabilistic approach and propagated using a Monte Carlo simulation technique. The methodological approach is illustrated on a case study which compares the sustainability of two options for electricity generation: coal versus biomass. Different models have been used to quantify their sustainability performance for a number of economic, environmental and social criteria. Three cases are considered with respect to uncertainty: (1) no uncertainty, (2) uncertainty in data/models and (3) uncertainty in models and decision-makers’ preferences. The results shows how characterising and propagating uncertainty can help increase the effectiveness of multi-criteria decision making processes and lead to more informed decision.     

Policy analysis and decision making in a network: how to improve the quality of analysis and the impact on decision making

In a network, parties have different interests and are interdependent. This hampers collective decision making. If, in such a network, a policy analysis is made to support the decision making, the findings from this analysis are likely to lack authority. For a policy analysis to be authoritative and to contribute to collective decision making, a process of interaction between the analyst and the parties concerned should be organized. This is called process management. This article presents a number of guidelines for such a process. They are based on two case studies into the use of policy analysis in networks.     

Using reliability analysis to support decision making in phased mission systems

Because of the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary decision diagrams (BDDs) offer fast, accurate reliability analysis that could contribute to real‐time decision making. However, phased mission analysis using existing BDD models is too slow to contribute to the instant decisions needed in time‐critical situations. This paper investigates 2 aspects of BDD models that affect analysis speed: variable ordering and quantification efficiency. Variable ordering affects BDD size, which directly affects analysis speed. Here, a new ordering scheme is proposed for use in the context of a decision‐making process. Variables are ordered before a mission, and reordering is unnecessary no matter how the mission configuration changes. Three BDD models are proposed to address the efficiency and accuracy of existing models. The advantages of the developed ordering scheme and BDD models are demonstrated in the context of their application within a reliability analysis methodology used to support decision making in an unmanned aerial vehicle.     

SMS for decision making of SMEs

To pursue the high environmental performance, economic and social effectiveness of the companies, including small and medium enterprises (SMEs), is the key goal of the sustainable development concept. Sustainable development is based on preventive management principles, and their application in SMEs has become an important issue for enhancing competitiveness. Unfortunately, most of the sustainable development-related research is focused on large companies rather than SMEs, especially in the industrial sector. The importance of SMEs often remains unnoticed. Besides, SMEs themselves often have inadequate knowledge about their environmental and social impacts and management, and apply voluntary preventive measures less frequently than large companies. To make sustainable decisions and to improve the environmental performance, economic and social effectiveness of SMEs, an integrated sustainable management system (SMS) based on financial analysis is necessary, oriented to strategic sustainability goals, not requiring significant financial and human resources. Integration of sustainability management accounting and composite sustainable development index methodologies forms the basis of SMS for SMEs decision making. SMS was applied in three pilot SMEs (small-scale wood parquet, medium-scale wood pallets, medium-scale beverage producing companies). In this article, an extensive analysis of a small-scale wood parquet manufacturing company’s case is presented. The application of SMS enabled to identify key sustainability problems and to find solutions to improve the companies’ sustainability performance. SMS application resulted in reduced input materials consumption and the reduction of sustainability costs.     

Decision criteria for the identification of alternatives in strategic environmental assessment

The European Union Strategic Environmental Assessment (SEA) Directive requires the assessment of likely significant effects on the environment of implementing plans or programmes and reasonable alternatives. While Irish SEA regulations and guidelines emphasise rigour and objectivity in the assessment of alternatives they have little to say on the actual identification of alternatives. Therefore, criteria should be established that would aid decision-makers in the identification of alternatives appropriate to the tier of decision-making. A methodology is set out in this paper for identifying generic SEA alternatives for a proposed plan or programme. Specifically, the methodology includes a set of alternatives identification criteria. The outputs from this methodology will help focus on the identification of more sustainable alternatives for SEA.     

Equivalence of decision problems

Summary A general and strong notion of equivalence of decision problems is given. Some results and examples are given to show that this natural notion is well adapted to the methodology of statistics. Part of this paper has been presented in the XVIII Reunión Nacional de Estadística, Investigación Operativa e Informática on September 1989 at Santiago University (Spain).