Ideal Point Method Research Articles

Multiobjective optimization of the cooling system of a marine diesel engine

AbstractAn intelligent cooling system directly influences the thermal load of high‐temperature components, heat distribution, and fuel economy of a diesel engine. An optimal coolant pump rotational speed map is a key factor in intelligent cooling control strategies. In this study, we designed an experimental variable coolant flow system for a maritime diesel engine. Experiment design and D‐optimal designs were used to optimize the parameters of the diesel engine cooling system. The diesel engine speed, load, and freshwater rotational pump speed were selected as variables. The temperature of the high‐thermal‐load zone of the combustion chamber components, fuel consumption rate, effective power, and peak cylinder pressure were selected as response variables, and the D‐optimal method was used to sample the experimental points. Polynomial response surface models were obtained using a stepwise algorithm. A multiobjective optimization problem was converted into a simple‐objective optimization problem using the ideal point method. A genetic algorithm was used to optimize the single‐objective function globally to obtain the optimal freshwater pump speed map for a diesel engine under all conditions. On average, the optimized cooling system decreased the fuel consumption by 1.901%. Six typical propulsive conditions were selected to confirm the validity of the optimization results. The experimental results indicate that the fuel consumption decreased by 2.35%, the effective power increased by 2.26%, and the power consumption of the water pump decreased by 17.83%. The combination of experiment design and D‐optimal designs offers the advantages of low cost, high efficiency, and high precision in solving multiobjective optimization problems involving strong coupling and nonlinear systems. The results of this research provide data support and a theoretical basis for intelligent cooling control strategies.

Assessing environmental water requirement for groundwater-dependent vegetation in arid inland basins by combining the copula joint distribution function and the dual objective optimization: An application to the Turpan Basin, China

Preserving groundwater-dependent terrestrial ecosystems through environmental water allocation is critical for sustainable development in arid inland basins. Assessing the environmental water requirement is challenging due to the complex relationship between vegetation growth and groundwater depth. This study proposed a new assessment method by combining the copula joint distribution function and the dual objective optimization. The copula joint distribution function was used to describe the relationship between vegetation and groundwater depth instead of the traditional regression analysis. Given an ecological protection target, the conditional probability of achieving the target was estimated using the copula joint distribution. The groundwater depth interval with relatively high probability was suitable for vegetation growth and correspondingly conducive for ecological protection. In addition to ecological protection, the socio-economic water requirement was incorporated into the environmental water assessment, resulting in a dual optimization problem that could be resolved by the ideal point method. The optimization analysis revealed a groundwater depth with a high probability of successful ecological protection and low groundwater evapotranspiration to balance vegetation and human demands for groundwater. The proposed method of environmental water assessment by combing copula joint distribution function and dual objective optimization was applied in the Turpan Basin, an arid inland basin in Northwest China. The environmental groundwater depth ranged between 6 and 20 m, and the optimized interval was 7–8 m. The optimal environmental groundwater depth resulted in a probability of 0.46 to achieve the ecological protection target and annual evapotranspiration of 983 mm. The proposed method was practical and reliable and could be an effective tool for assessing the environmental water requirement of groundwater-dependent vegetation in arid inland basins.

Optimal Design of the Shape of a Non-Ball Mandrel for Thin-Walled Tube Small Radius Cold Bending

In the field of cold bending, it is necessary to use ball mandrels, especially to bend thin-walled tubes with a small radius. However, the bending process with a ball mandrel is complex and expensive, and it is easy to jam the core ball inside the tube. To solve these issues, we designed two kinds of hollow non-ball mandrel schemes with low stiffness that were suitable for the small radius bending of thin-walled tubes. We evaluated the forming quality of cold bending numerically and the influence of the hollow section length and thickness on the forming indices. Our results showed that the thickness of the hollow section has a greater influence on forming quality than the length. As the hollow section’s thickness increased, the wrinkling rate first declined by approximately 40% and then increased by above 50%. When the thickness was 11 mm in scheme 1 and 13 mm in scheme 2, the wrinkling rate reached minimum values of 1.32% and 1.50%, respectively. As the hollow section’s thickness increased, the flattening rate decreased by more than 60% and the thinning rate increased by about 40%. A multi-objective optimization of forming indices was carried out by ideal point method and grey wolf optimizer. By comparing the forming results before and after optimization, the feasibility of using the proposed hollow mandrel was proved, and the hollow mandrel scheme of standard cylinder is therefore recommended.

Empirical Analysis of the Matching Degree between Energy Equipment Manufacturing and Market Demand: A Global Perspective

The study of matching degree between energy equipment manufacturing and market demand is crucial for energy enterprises to adjust business strategies, expand market share, and develop sustainably. Considering that the current electricity market evaluation indicators are rarely selected from a global perspective and a single evaluation method may lead to one-sided results, this article takes the technology and equipment related to electric energy as the research object and selects six indicators, including technical standards, qualification certification, export methods, after-sales service, market concentration, and product concentration. By analyzing the supply and demand characteristics of major global regional markets and the situation of Chinese power enterprises in these markets, we propose matching model cluster including osculating value method, rank-sum ratio method, ideal point method, entropy value method, and efficacy coefficient method to conduct the matching degree study. The results show that the overall market matching degree of Chinese power companies is good, especially in Southeast Asia, Central Asia, and Africa. For markets with a low degree of matching, we analyze the reasons based on the matching indicators values to provide companies with corresponding strategies and recommendations.

Measuring Toronto's vital signs – Comparing global and local ideal point analysis in an urban equity case study

Multi-Criteria Decision Analysis (MCDA) offers a unique analytical lens for examining socio-economic indicators within cities. Competing, interrelated criteria are combined to produce a single weighted score for each location or spatial unit. The Toronto Foundation's Vital Signs report provides an annual snapshot of Toronto's quality of life, using ten indicator categories. While the report is published at a city scale, a spatially explicit approach could offer a deeper interpretation of the results. While global MCDA methods can conceal geographic variation, novel local techniques account for spatial heterogeneity in relevant characteristics. In this paper, a localized ideal point method, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), was applied to the Vital Signs report. The results show more variation and less spatial autocorrelation than the global approach and a simplified representation of the report. GIS researchers are increasingly exploring local MCDA approaches using vector data, but the more complex techniques such as TOPSIS are relatively underdeveloped. This case study aims to fill this conceptual gap and illustrate the applicability of local ideal point analysis in an urban equity context.

Crashworthiness analysis and multi-objective optimization for honeycomb structures under oblique impact loading

Oblique impact loading conditions are unavoidable in practical applications, which strongly influence the performance response of energy-absorbing structures. In this paper, the finite element models of four typical cellular structures (hexagon honeycomb, re-entrant hexagon honeycomb, star-shape honeycomb, double arrow honeycomb) are established and experimentally validated. The dynamic responses of four structures under different impact angles (from 0 to 30°) and impact velocities (from 5 to 50 m/s) are investigated. On this basis, the influences of impact angle and impact velocity on the specific energy absorption (SEA) and peak crushing force (PCF) of four structures are discussed. The results reveal that the negative Poisson’s ratio structure has the advantage of energy absorption under axial impact due to the characteristics of compression and contraction at the low impact velocity. The hexagonal honeycomb structure has great advantages in terms of comprehensive energy absorption capacity and better stability at varying inclination angles. The Non-dominated Sorting Genetic Algorithm (NSGA-II) coupled with the ideal point method (IPM) is utilised to explore the optimal design of hexagon honeycomb structure, which is then verified by a detailed crashworthiness comparison with the original design. The optimal honeycomb structure shows excellent crashworthiness characteristics and demonstrates great potential for applications in impact engineering, especially the oblique impact loading situations.

Rockburst prediction for hard rock and deep-lying long tunnels based on the entropy weight ideal point method and geostress field inversion: a case study of the Sangzhuling Tunnel

To evaluate rockbursts in deep-lying long tunnels, a multiple factor analysis and predictions were conducted. It is necessary to establish whether the primary evaluation indexes cover the entire development–occurrence–evolution process for rockbursts and how best to determine the weights of the final selected indexes. We developed an evaluation model with attribute reduction and chose 5 out of 11 primary evaluation indexes to cover the typical characteristics of energy storage, rockburst proneness, and risk of failure. The weights of the primary evaluation indexes and the offset distance were then determined using the entropy weight ideal point method. Combining geostress field inversion and rock mechanic tests, the evaluation model was applied to the case of the Sangzhuling Tunnel along the Sichuan–Tibet railway. Rockburst prediction results achieved 41.2% and 94.1% accuracy when using the Manhattan and Euclidean distance functions, respectively. A more specific classification of the evaluation indexes may optimize the weight assignment and help obtain more accurate results. This paper provides a reliable method for rockburst predictions for hard rock and deep-lying long tunnels, which may have good prospects for engineering applications.

Multi-objective lightweight and crashworthiness collaborative optimisation of commercial vehicle cab

A collaborative optimisation method for the lightweight and crashworthiness of the cab structure is proposed using mixed variable screening, approximate models, multi-objective optimisation and ideal point methods. First, modal and stiffness analyses of the cab model are built. Three impact simulation model of cab are established and verified via ECE R29-02 regulation tests. Subsequently, front impact, front pillar impact, and roof strength model are established following ECE R29-03, which is more stringent than the ECE R29-02. However, the result of the front pillar impact of the cab does not meet the requirements of the ECE R29-03. Several improved A-pillar structures are proposed, among which reinforced rib structure can effectively enhance the occupant’s living space. Then, 18 thickness and 4 material variables are selected as design variables based on the mixed variable screening method. Different approximate models are established for performance responses. The results show that the second-order response surface model has high fitting accuracy in the cab modal and bending and torsional stiffness performance, while the Kriging model has high fitting accuracy in the crashworthiness indicators of the cab. Finally, the multi-objective lightweight and crashworthiness collaborative optimisation of the cab are conducted. Compared with the initial model, the crashworthiness of the optimal cab model is improved and the mass is reduced by 27.1 kg.

Model on Improved Variable Weight-Matter Element Theory for Risk Assessment of Water Inrush in Karst Tunnels

This paper presents an improved risk assessment model to evaluate the risk of water inrush in karst tunnels based on matter element theory and ideal point method. The 4 first-grade evaluation indexes and 13 s-grade factors are selected to establish the evaluation index system by considering the occurrence conditions of water inrush. All second-grade evaluation indexes are quantitatively divided into four risk grades. Based on improved Analytical Hierarchy Process and Triangular Fuzzy Number, the constant weights are obtained. The variable weights are determined according to the state variable weight theory and the values of evaluation indexes. The risk grade of water inrush is recognized by the closeness degree analysis. The proposed risk assessment model was applied to 3# inclined shaft of Yuelongmen tunnel, and the accuracy of the assessment result was verified by comparing with advance geological forecast and excavation. This proposed model provides a practical tool to evaluate the risk of water inrush in karst tunnels.

Green Supply Chain Network Optimization Under Random and Fuzzy Environment

This paper established a three-level supply chain composed of plants, distribution centers, and retailers, and studied the location of distribution centers in the supply chain network and the carbon emissions during processing and transportation. In a random and fuzzy environment, the research objective is to minimize the supply chain’s cost and carbon emission. The multi-objective uncertain equilibrium model of the green supply chain network is established by introducing opportunity constraints, and the stability of the model can be enhanced by using variance function and risk function. Then this research integrated the theory of stochastic programming and fuzzy mathematical programming and employed Monte Carlo simulation; the sample mean approximation, chance-constrained programming and fuzzy expectation to deal with the random parameters and fuzzy parameters in the model so that the uncertain model is clarified. Further, the authors used the hierarchical method, the weighted ideal point method, restriction method, and weighted ideal point method to solve the multi-objective model. Finally, a numerical example is provided to demonstrate the feasibility of the model.

Multiobjective optimization of building energy consumption based on BIM-DB and LSSVM-NSGA-II

The building envelope performance significantly influences the building energy consumption, and the major influencing factors of the building envelope include the external wall U-value, external wall solar absorptance, roof U-value, roof solar absorptance, external window U-value, and window-to-wall ratio. This paper proposed a framework that integrates Building Information Modeling (BIM) with LSSVM (least square support vector machine (LSSVM) and non-dominated sorting genetic algorithm-II (NSGA-II) to study the influence of building envelope parameters on building energy consumption and discover the best design. The DesignBuilder (DB) is used to perform energy consumption simulation and orthogonal experiment to obtain the sample data set. The LSSVM is utilized to learn the data set to establish a prediction model between the building envelope and energy consumption, which is used as the fitness function of the building energy consumption in NSGA-II. With the objective of minimizing building energy consumption and maximizing the indoor thermal comfort (measured by predicted mean vote or PMV), an NSGA-II multi-objective optimization model is established. The Pareto front is obtained through calculation, and the optimal combination of building envelope parameters is discovered using the ideal point method. A case of a proposed school building in China is used to demonstrate the feasibility and effectiveness of the developed framework, the results show that: (1) The LSSVM has great ability to predict building energy consumption, achieving an accurate prediction with a goodness-of-fit of 0.9549 and an RMSE of 0.0273; (2) The optimized envelope design parameters of the proposed building are presented, including the External wall U-value is 0.2, the External wall solar absorptance is 0.55, the Roof U-value is 0.2, the External window U-value is 0.4166, the External window U-value is 1, the Window-wall ratio is 0.215. (3) The developed LSSVM-NSGA II hybrid approach can effectively improve the building’s energy consumption and thermal comfort with the building energy consumption reduced by 10.6% and the thermal comfort increased by 32.2% than the initial values, respectively. The proposed LSSVM-NSGA II framework is able to optimize building envelope design parameters than its precedent, which can provide effective thinking for similar problems.

A Group-Decision-Making Framework for Evaluating Urban Flood Resilience: A Case Study in Yangtze River

Floods are among the most common and destructive natural disasters confronted by cities and are further aggravated by rapid climate change and increasing urbanization, posing a great challenge to flood risk management. To cope with uncertainty, there is a need to move towards approaches to managing flood risk by taking resilience into consideration. While the evaluation of urban flood resilience has gained much attention in recent decades, studies on quantitative measurement using multiple criteria decision making (MCDM) approaches are rare. In addition, the results determined by different MCDM methods may exhibit considerable variability. It is an intractable task to gather a group consensus from these methods. In this regard, in this paper, we propose a group-decision-making framework for measuring urban resilience to flooding, combining three stages, which are (i) normalizing the data, (ii) weighting the criteria and (iii) aggregating the results. Four objective MCDM methods—i.e., the variation coefficient method, Shannon weighting method, CRITIC and ideal point method—are proposed and treated as reliable methods. A stochastic multi criteria acceptability analysis is adopted to integrate those results into a composite resilience index. The proposed methodology is applied to the resilience evaluation problem of 41 cities in the Yangtze River basin, and the results are compared with those obtained with the four MCDM methods. It is demonstrated that our method considers all possible preferences among the results provided by various MCDM methods and is thus more robust and acceptable.

Research on comprehensive evaluation of quality performance of all employees in electronic equipment enterprises based on entropy method and ideal point method

The overall quality evaluation of electronic equipment is helpful to improve product quality and has become an important focus of quality control. Based on the systematic analysis of job characteristics of all employees, sixteen index frames are constructed from four dimensions of knowledge quality, key quality performance, quality reward and punishment and quality innovation. Secondly, the fuzzy value conversion method is designed with the characteristics of the evaluation index value of electronic equipment, the objective weight is determined by the entropy method, and comprehensive evaluation model is also designed by ideal point method. Finally, a case is given to illustrate the implementation process and feasibility of the proposed method, which can provide theoretical and practical guidance for improving quality performance of all employees.

ПРИНЯТИЕ РЕШЕНИЯ ПО ВЫБОРУ ТИПА УКРЕПЛЕНИЯ ВОДООТВОДНЫХ И НАГОРНЫХ КАНАВ НА ОСНОВЕ МЕТОДА ИДЕАЛЬНОЙ ТОЧКИ

Modern materials and technologies for strengthening drainage and upland ditches, their advantages and disadvantages are considered. When choosing the type of reinforcement, the railway design engineer must compare the options for the types of reinforcement of ditches in terms of various criteria: reducing labour and resource intensity, duration of construction work, increasing durability, improving environmental friendliness, the need for special equipment, and others. An ideal point method is proposed for solving a multicriteria deterministic problem of choosing the type of ditch reinforcement. A prototype program of the decision support system for choosing the type of reinforcement using the ideal point method has been developed. The program contains four areas: the source data area; the calculation area; the guide to the types of ditch reinforcement, which separately identifies innovative types of ditch reinforcement; the area of calculation results and recommendations. With the help of the program, the test problem of choosing the type of reinforcement is solved. Of the three alternatives, a concrete roadbed is recommended-an innovative strengthening of the ditch.

A fuzzy multi-objective programming optimization model for emergency resource dispatching under equitable distribution principle

In the initial stage of emergency rescue for major railway emergencies, there may be insufficient emergency resources. In order to ensure that all the emergency demand points can be effectively and fairly rescued, considering the fuzzy properties of the parameters, such as the resource demand quantity, the dispatching time and the satisfaction degree, the railway emergency resources dispatching optimization model is studied, with multi- demand point, multi-depot, and multi-resource. Based on railway rescue features, it was proposed that the couple number of relief point - emergency point is the key to affect railway rescue cost and efficiency. Under the premise of the maximum satisfaction degree of quantity demanded at all emergency points, a multi-objective programming model is established by maximizing the satisfaction degree of dispatching time and the satisfaction degree of the couple number of relief point - emergency point. Combined with the ideal point method, a restrictive parameter interval method for optimal solution was designed, which can realize the quick seek of Pareto optimal solution. Furthermore, an example is given to verify the feasibility and effectiveness of the method.

A Novel Evaluation Model of Grouting Effect in Weak and Water-Rich Stratum

The development of underground engineering promotes the development of grouting technology, but due to its particularity, the research of grouting theory lags behind the application requirements of actual engineering, and the evaluation of grouting effect is a weak link in grouting theory. Grouting effect is influenced by many factors with uncertainty and nonlinear characteristics. Four factors, anti-inference method of slurry filling rate, displacement monitoring method, exposure observation method, core method in access hole, were proposed, and the corresponding quantitative indexes were determined. In this study, a novel evaluation model was developed using analytic hierarchy process and ideal point method to study grouting effect in weak and water-rich stratum. The results show that this method is feasible. With its strong operability, the proposed method provides a new means to evaluate grouting effect.

Evaluation and Optimization of Human Resource Supply in Packaging Design Project

In order to solve the problem of selection of human resource provider for the demander in package design project, firstly, the evaluation index system of provide side is established, and the entropy weight method is used to calculate the objective weight of the evaluation index; secondly, the subjective weight is solved by the five scale valuation method, and the comprehensive weight with subjective and objective significance is obtained; then, with the help of the ideal point method, the provide side is evaluated, which can provide a reference for the choice of the demander; finally, an example is given to verify the effectiveness and practicability of the method.

Modeling oasis dynamics driven by ecological water diversion and implications for oasis restoration in arid endorheic basins

To achieve sustainable development, ecological water diversion has been implemented as a management tool to recover degraded oasis ecosystems in arid endorheic basins. Aiming to explore oasis response and identify appropriate objectives for oasis restoration, this study used a conceptual lumped ecohydrological model. Qingtu Oasis in the Shiyang River basin, Northwest China, was used as a case study to test this model. The model coupled groundwater budget, oasis response, and evapotranspiration dynamic modules. The model structure was clear and reasonable, and the calculation was of low cost. The application in Qingtu Oasis verified the model's effectiveness. The model was able to effectively capture the ecohydrological response attributed to the recovering of Qingtu Oasis in response to ecological water diversions occurring during the last decade. Combined with scenario analysis, the simulation indicated that Qingtu Oasis was fragile and largely dependent on ecological water diversion. Ecological responses were positive and non-linearly correlated with water input, resulting in an optimal water input that produced maximum water benefit by minimum water consumption. The ideal point method was useful in identifying this cost-effective water volume for oasis restoration. For Qingtu Oasis, the optimal water diversion was 45 million m3, which would recover the oasis to 29.16 km2 with an NDVI of 0.41. The current oasis conditions approach the optimal status, and ecological water diversion was suggested to continue and maintain the current oasis status. The volume of 45 million m3 could be taken as an upper threshold of water diversion, because above this threshold, water consumption would not result in water benefits effectively. This study proposed a practical tool for ecohydrological process simulation.

Study on the optimization of urban passenger traffic structure based on multi-objective linear programming-a case study of Beijing.

With the increasing number of car trips in cities, energy consumption and environmental pollution have become key issues in urban transportation. In particular, the increasing use of private cars not only leads to more energy consumption and produces more waste gas, but also makes the traffic structure unbalanced. Therefore, it is necessary to establish and optimize the reasonable traffic structure in order to promote the sustainable development of urban traffic. Based on the characteristics of different transportation modes, this paper proposes a multi-objective optimization model that maximizes transportation utility, minimizes ecological impact, and minimizes generalized cost. The ideal point method, linear weighting method, and hierarchical sequence method were used to solve and compare the model. It has been concluded that the ideal point method is more suitable for the research of this paper and can be applied to optimize the traffic structure of Beijing. Through example analysis, the optimized urban passenger traffic turnover and sharing rate are more scientific and reasonable, which verifies the feasibility of the model. This model not only guarantees the interests of passengers and reduces carbon emissions, it also maximizes the utility of urban traffic and the lowest generalized cost. It reflects the concept of sustainable development of urban transportation. Finally, we are able to make reasonable suggestions to relevant departments based on the optimization results.

Fuzzy clustering of homogeneous decision making units with common weights in data envelopment analysis

Data Envelopment Analysis (DEA) is the most popular mathematical approach to assess efficiency of decision-making units (DMUs). In complex organizations, DMUs face a heterogeneous condition regarding environmental factors which affect their efficiencies. When there are a large number of objects, non-homogeneity of DMUs significantly influences their efficiency scores that leads to unfair ranking of DMUs. The aim of this study is to deal with non-homogeneous DMUs by implementing a clustering technique for further efficiency analysis. This paper proposes a common set of weights (CSW) model with ideal point method to develop an identical weight vector for all DMUs. This study proposes a framework to measuring efficiency of complex organizations, such as banks, that have several operational styles or various objectives. The proposed framework helps managers and decision makers (1) to identify environmental components influencing the efficiency of DMUs, (2) to use a fuzzy equivalence relation approach proposed here to cluster the DMUs to homogenized groups, (3) to produce a common set of weights (CSWs) for all DMUs with the model developed here that considers fuzzy data within each cluster, and finally (4) to calculate the efficiency score and overall ranking of DMUs within each cluster.