A Class of Optimization Method for Bilevel Multi-objective Decision Making Problem with the Help of Satisfactoriness

In the paper, it is discussed that the method on how to transform the multi-person bilevel multi-objective decision making problem into the equivalent generalized multi-objective decision making problem by using Kuhn-Tucker sufficient and necessary condition. In order to embody the decision maker′s hope and transform it into single-objective decision making problem with the help of ε-constraint method. Then we can obtain the global optimal solution by means of simulated annealing algorithm.

A decision support system for satellite layout integrating multi-objective optimization and multi-attribute decision making

A decision support system, including a multi-objective optimization framework and a multi-attribute decision making approach is proposed for satellite equipment layout. Firstly, given three objectives (to minimize the C.G. offset, the cross moments of inertia and the space debris impact risk), we develop a threedimensional layout optimization model. Unlike most of the previous works just focusing on mass characteristics of the system, a space debris impact risk index is developed. Secondly, we develop an efficient optimization framework for the integration of computer-aided design (CAD) software as well as the optimization algorithm to obtain the Pareto front of the layout optimization problem. Thirdly, after obtaining the candidate solutions, we present a multi-attribute decision making approach, which integrates the smart Pareto filter and the correlation coefficient and standard deviation (CCSD) method to select the best tradeoff solutions on the optimal Pareto fronts. Finally, the framework and the decision making approach are applied to a case study of a satellite platform.

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.

Forest use suitability:Towards decision-making-oriented sustainable management of forest ecosystem services

Management of forest lands considering multi-functional approaches is the basis to sustain or enhance the provi-sion of specific benefits,while minimizing negative impacts to the environment.Defining a desired management itinerary to a forest depends on a variety of factors,including the forest type,its ecological characteristics,and the social and economic needs of local communities.A strategic assessment of the forest use suitability(FUS)(namely productive,protective,conservation-oriented,social and multi-functional)at regional level,based on the provision of forest ecosystem services and trade-offs between FUS alternatives,can be used to develop management strategies that are tailored to the specific needs and conditions of the forest.The present study assesses the provision of multiple forest ecosystem services and employs a decision model to identify the FUS that sup-ports the most present and productive ecosystem services in each stand in Catalonia.For this purpose,we apply the latest version of the Ecosystem Management Decision Support(EMDS)system,a spatially oriented decision support system that provides accurate results for multi-criteria management.We evaluate 32 metrics and 12 as-sociated ecosystem services indicators to represent the spatial reality of the region.According to the results,the dominant primary use suitability is social,followed by protective and productive.Nevertheless,final assignment of uses is not straightforward and requires an exhaustive analysis of trade-offs between all alternative options,in many cases identifying flexible outcomes,and increasing the representativeness of multi-functional use.The assignment of forest use suitability aims to significantly improve the definition of the most adequate management strategy to be applied.

Decision making tools for optimal material selection:A review

The present work reviews different decision making tools(material comparing and choosing tools)used for selecting the best material considering different parameters.In this review work,the authors have tried to address the following important enquiries:1)the engineering applications addressed by the different material choosing and ranking methods;2)the predominantly used decision making tools addressing the optimal material selection for the engineering applications;3)merits and demerits of decision making tools used;4)the dominantly used criteria or objectives considered while selecting a suitable alternative material;5)overview of DEA on material selection field.The authors have surveyed literatures from different regions of the globe and considered literatures since 1988.The present review not only stresses the importance of material selection in the early design stage of the product development but also aids the design and material engineers to apply different decision making tools systematically.

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.

A Direct-Indirect Cost Decision Making Assessment Methodology for Seismic Isolation on Bridges

Making decisions of when to intervene on bridges taking into consideration more than owner costs is a growing field of interest in earthquake engineering. In particular, bridges can be considered critical links in highway networks because of their seismic vulnerability in terms of direct and indirect losses. This paper aims at defining a general criteria capable of taking into account both these costs in a simplified and efficient formulation. Indirect losses generally neglected elsewhere, are taken into consideration by applying a formulation that assesses investment efficiency. The presented formulation follows the one proposed for buildings by L. Kantorovich, 1975. Direct costs are computed from a Performance Based Earthquake Engineering （PBEE） methodology by the Pacific Earthquake Engineering Research （PEER） center. The problem considers two competitive objectives （maximizing economic efficiency and minimizing costs） in a multi-objective structural optimization procedure. The formulation has been applied to a case study aimed at strengthening a benchmark bridge. The optimum investment has been assessed between several isolated configurations.

A Multi-Criteria Decision Making for the Unrelated Parallel Machines Scheduling Problem

In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a produc-tion environment involving several unrelated parallel machines and we will focus on three objectives: minimizing makespan, total flow time, and total number of tardy jobs. The decision making method consists of three phases. In the first phase, a mathematical model of a single machine scheduling problem, of which the objective is a weighted sum of the three objectives, is constructed. Such a model will be repeatedly solved by the CPLEX in the proposed Multi-Objective Simulated Annealing (MOSA) algorithm. In the second phase, the MOSA that integrates job clustering method, job group scheduling method, and job group – machine assignment method, is employed to obtain a set of non-dominated group schedules. During this phase, CPLEX software and the bipartite weighted matching algorithm are used repeatedly as parts of the MOSA algorithm. In the last phase, the technique of data envelopment analysis is applied to determine the most preferable schedule. A practical example is then presented in order to demonstrate the applicability of the proposed decision making method.

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.

Stability Analysis and Efficiency Improvement of a Multi-converter System Using Multi-objective Decision Making

Multi-converter system is mainly used in advanced automotive systems.Different converters and inverters are taking part in automotive systems to provide different voltage levels in a multi-converter system.It involves constant voltage load(CVL),constant power load(CPL)and other loads.The CPL in such systems offers negative impedance characteristic and it creates a destabilizing effect on the main converter.The effect of destabilization can be reduced by increasing the CVL or inserting parasitic components.Attempts have been made by authors to improve the stability by using parasitics of different components such as switch,diode and inductor.Influence of insertion of parasitics including the series equivalent resistance of the filter capacitor and variation in CVL on the performance of main converter is mathematically analyzed and conflicting behavior between system stability and efficiency is observed.The optimum solution between these two functions is obtained by using multi-objective decision making(MODM)by varying parasitics of different components and CVL.An attempt has been made to demonstrate the effect of CVL load and the parasitics on the stability and efficiency of the main converter,experimentally.

Co-optimization of carbon dioxide storage and enhanced oil recovery in oil reservoirs using a multi-objective genetic algorithm(NSGA-Ⅱ)

Climate researchers have observed that the carbon dioxide （CO2） concentration in the atmosphere have been growing significantly over the past century. CO2 from energy represents about 75% of the greenhouse gas （GHG） emissions for Annex B （Developed） countries, and over 60% of global emissions. Because of impermeable cap rocks hydrocarbon reservoirs are able to sequester CO〉 In addition, due to high-demand for oil worldwide, injection of CO2 is a useful way to enhance oil production. Hence, applying an efficient method to co-optimize CO2 storage and oil production is vital. Lack of suitable optimization techniques in the past led most multi-objective optimization problems to be tackled in the same way as a single objective optimization issue. However, there are some basic differences between the multi and single objective optimization methods. In this study, by using a non- dominated sorting genetic algorithm （NSGA-II） for an oil reservoir, some appropriate scenarios are proposed based on simultaneous gas storage and enhanced oil recovery optimization. The advantages of this method allow us to amend production scenarios after implementing the optimization process, by regarding the variation of economic parameters such as oil price and CO2 tax. This leads to reduced risks and time duration of making new decisions based on upcoming situations.

A Multi-Objective Obnoxious Facility Location Modelon a Plane

In this paper a Vertex Covering Obnoxious Facility Location model on a Plane has been designed with a combination of three interacting criteria as follows: 1) Minimize the overall importance of the various exist-ing facility points;2) Maximize the minimum distance from the facility to be located to the existing facility points;3) Maximize the number of existing facility points covered. Area restriction concept has been incor-porated so that the facility to be located should be within certain restricted area. The model developed here is a class of maximal covering problem, that is covering maximum number of points where the facility is within the upper bounds of the corresponding mth feasible region Two types of compromise solution methods have been designed to get a satisfactory solution of the multi-objective problem. A transformed non- linear programming algorithm has been designed for the proposed non-linear model. Rectilinear dis-tance norm has been considered as the distance measure as it is more appropriate to various realistic situa-tions. A numerical example has been presented to illustrate the solution algorithm.

Multi-objective optimization based optimal setting control for industrial double-stream alumina digestion process

The operation variables,including feed rate of ore slurry,caustic solution and live steams in the double-stream alumina digestion process,determine the product quality,process costs and the environment pollution.Previously,they were set by the technical workers according to the offline analysis results and an empirical formula,which leads to unstable process indices and high consumption frequently.So,a multi-objective optimization model is built to maintain the balance between resource consumptions and process indices by taking technical indices and energy efficiency as objectives,where the key technical indices are predicted based on the digestion kinetics of diaspore.A multi-objective state transition algorithm(MOSTA)is improved to solve the problem,in which a self-adaptive strategy is applied to dynamically adjust the operator factors of the MOSTA and dynamic infeasible threshold is used to handle constraints to enhance searching efficiency and ability of the algorithm.Then a rule based strategy is designed to make the final decision from the Pareto frontiers.The method is integrated into an optimal control system for the industrial digestion process and tested in the actual production.Results show that the proposed method can achieve the technical target while reducing the energy consumption.

Synergetic Optimization of Missile Shapes for Aerodynamic and Radar Cross-Section Performance Based on Multi-objective Evolutionary Algorithm

A multiple-objective evolutionary algorithm (MOEA) with a new Decision Making (DM) scheme for MOD of conceptual missile shapes was presented, which is contrived to determine suitable tradeoffs from Pareto optimal set using interactive preference articulation. There are two objective functions, to maximize ratio of lift to drag and to minimize radar cross-section (RCS) value. 3D computational electromagnetic solver was used to evaluate RCS, electromagnetic performance. 3D Navier-Stokes flow solver was adopted to evaluate aerodynamic performance. A flight mechanics solver was used to analyze the stability of the missile. Based on the MOEA, a synergetic optimization of missile shapes for aerodynamic and radar cross-section performance is completed. The results show that the proposed approach can be used in more complex optimization case of flight vehicles.

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.

An Importance Segregation Based Multi-Objective Optimization Model for Traffic Safety Improvement Countermeasure Selection

This paper presents a multi-objective optimization model to decide effective and beneficial portfolio for implementing traffic safety improvements under budgetary constraints.Different from the conventional multi-objective approaches,the proposed model segregates decision criteria into different importance levels and designs a successive optimization approach to obtain the final solution(s).Such modeling features offer the advantages to:1)prevent the arbitrariness for transportation agencies to determine weights for decision criteria;2)remedy the deficiency of over-weighting less important criteria in the traditional multi-objective optimization approach;and 3)minimize the number of potential solutions for final decision by transportation agencies with enhanced screening of the sub-optimal solutions.Case study results reveal that the proposed model is efficient not only for deciding the most suitable traffic safety countermeasure for a specific site,but also for determining the plans for implementing multiple countermeasures among multiple sites given the budget constraint.Comparative study results have also indicated that the proposed model outperforms the traditional criteria in objectively selecting traffic safety improvements in a multi-criteria decision-making process.The clarity of model inputs and the interpretation of results with respect to different selection criteria offer its best potential to be used as an effective decision-support tool for transportation authorities to assess and refine their safety improvement investments.

环境友好型城网规划双层决策模型及其协调局势算法

构建环境友好型城市电网,全面系统地量化环境属性,是新形势下城网规划决策面临的重要问题。通过深入剖析环境友好型城市电网的内涵及其对环境影响的内在原理,建立了一个能够适应环境友好型规划理念的新型城市电网规划双层决策模型。首先,从环境友好型电网的内涵出发,在量化可靠性、经济性、生态压力、环境效应、资源消耗以及美学性等6个维度基础上,设计提出了环境友好型城网规划双层评价指标体系及其具体评估模型;其次,根据双层多目标递阶优化原理,研究并设计了一种基于协调局势的环境友好型城网规划分级决策模型求解算法;最后,利用实际算例验证了模型的合理性和可行性,并为未来智能电网环境下的城网规划建设提供了一些有益的理论参考。

基于随机二层规划的不确定电力市场中交互式模糊竞价决策方法

针对不确定的电力现货市场中发电商选择合约电量及合约电价,售电商确定合约电量及其现货交易量使他们获得最大经济效益的问题,建立了随机二层规划的理论模型,并在此模型的基础上提出了交互式模糊决策求解算法,从而探讨了不确定的电力现货市场中的竞价策略,得到了发电商和售电商关于长期合约交易与现货交易之间的进行最佳选择策略的方法.最后用实例验证了提出的模型和算法.

求解具0－1变量的两级决策问题的分枝－定界优化方法

在一类具０－１变量的两级决策问题基础上，研究了求解该问题的分枝－定界优化方法，分析了算法中定界的设计和分枝准则的选择。文中示例的仿真结果表明，该算法是有效的。

求解二层规划的一种模糊交互式方法(英文)

主要讨论上下层具有共同决策变量的一类二层规划问题的求解方法.在引入目标函数的模糊目标,并充分考虑上层与下层决策者的满意度后,构造了一个模糊交互式决策方法,从而使得上下层决策者对最后的求解结果都能满意.数值结果表明此法可行有效.