Multiple Objective Decision Research Articles

Maintenance decision making model with multiple attribute optimization

An effective maintenance schedule can largely improve productivity and reduce maintenance costs for enterprises. Many factors, such as resource, production, cost and crew, should be considered when we make maintenance plans. However, it is difficult to meet all requests of the production targets in practical engineering. The multiple attribute decision making for equipment maintenance is proposed in this paper, and the multiple objectives decision making method is utilized to solve the problem in the maintenance process. In the particular environment and resources, a case is studied to illustrate the model and methods. The model gives the optimal maintenance plan with the analytic hierarchy process method in accordance with the particular criteria. It has been proved that this model and decision methods are scientific and operable.

An Optimized Mathematical Model for Items Supplies Planning of a Logistic System

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.

An Energy-Efficient Skyline Query for Massively Multidimensional Sensing Data.

Cyber physical systems (CPS) sense the environment based on wireless sensor networks. The sensing data of such systems present the characteristics of massiveness and multi-dimensionality. As one of the major monitoring methods used in in safe production monitoring and disaster early-warning applications, skyline query algorithms are extensively adopted for multiple-objective decision analysis of these sensing data. With the expansion of network sizes, the amount of sensing data increases sharply. Then, how to improve the query efficiency of skyline query algorithms and reduce the transmission energy consumption become pressing and difficult to accomplish issues. Therefore, this paper proposes a new energy-efficient skyline query method for massively multidimensional sensing data. First, the method uses a node cut strategy to dynamically generate filtering tuples with little computational overhead when collecting query results instead of issuing queries with filters. It can judge the domination relationship among different nodes, remove the detected data sets of dominated nodes that are irrelevant to the query, modify the query path dynamically, and reduce the data comparison and computational overhead. The efficient dynamic filter generated by this strategy uses little non-skyline data transmission in the network, and the transmission distance is very short. Second, our method also employs the tuple-cutting strategy inside the node and generates the local cutting tuples by the sub-tree with the node itself as the root node, which will be used to cut the detected data within the nodes of the sub-tree. Therefore, it can further control the non-skyline data uploading. A large number of experimental results show that our method can quickly return an overview of the monitored area and reduce the communication overhead. Additionally, it can shorten the response time and improve the efficiency of the query.

Analysis of FM/FM/c queuing system: using fuzzy approach and parametric nonlinear programming

Applying fuzzy principles and approaches to the queue systems will provide more extensive and realistic applications of them. A queue system of M/M/c is studied based on fuzzy approach in this paper. This system was proposed as a FM/FM/c system with probability of the presence of customers in the system and utility factor. In addition, performance measurement was developed using the concept of parametric nonlinear programming and characteristics of fuzzy numbers. For further analysis, a FM/FM/c queuing system was considered to determine most appropriate value for the number of servers by using the concept of fuzzy relations and inference and fuzzy multiple objective decision making. The results of this research show that we can determine appropriate number of servers and we can do it perfectly and actually analyse based on system situations and management preferences.

A Multiple Objective Mathematical Program to Determine Locations of Disaster Response Distribution Centers

Every year, natural disasters kill thousands of people and affect millions of people as well as causing economic damages. This increasing number of affected people by disasters reveals the need for effective and efficient disaster response operations. This study focus on one of the important disaster response operations: the location of disaster response distribution centers. A multiple objective decision model is proposed to locate the main and local distribution centers simultaneously. The objectives of the model are minimizing distance among demand points, local, and main distribution centers, and minimizing the number of local distribution centers and main warehouses. The proposed model is solved for different instances (different number of candidate demand points, local and main distribution centers) using a goal programming approach. Although the initial results are promising, the completion time increases dramatically as the size of the problem increases.

Coalition fuzzy stability analysis in the Graph Model for Conflict Resolution

Coalition fuzzy stability concepts are developed within the Fuzzy Preference Framework for the Graph Model for Conflict Resolution to investigate how decision makers can cooperate. The objective is to identify favorable outcome(s) in a multiple participant-multiple objective decision problem with fuzzy preference information. More specifically, coalition versions of fuzzy Nash stability, fuzzy general metarationality, fuzzy symmetric metarationality, and fuzzy sequential stability are proposed. They constitute a natural generalization of the corresponding non-cooperative fuzzy preference-based definitions for Nash stability, general metarationality, symmetric metarationality, and sequential stability, respectively. Coalition fuzzy stability definitions are employed to analyze an actual dispute over groundwater contamination in Elmira, Ontario, Canada, demonstrating how these new concepts can be conveniently applied to practical problems in order to gain valuable strategic insights.

Whole Systems Trade Analysis

AbstractGround vehicles are complex systems with many interrelated subsystems – finding the sweet‐spot among competing objectives such as performance, unit cost, operations and sustainment (O&S) costs, development risk, and growth potential is a non‐trivial task. Whole Systems Trade Analysis (WSTA) is a systems analysis and decision support methodology and tool that integrates otherwise separate subsystem models into a holistic system view mapping critical design choices to consequences relevant to stakeholders. WSTA projects are highly integrated and collaborative efforts which generate holistic systems and Multiple Objective Decision Analysis (MODA) models. The related tool captures and synthesizes subsystem and system level analyses into trade‐space visualizations designed to facilitate rapid and complete understanding of the trade‐space to stakeholders and provide drill down capability to supporting rationale. The approach has opened up trade space exploration significantly evaluating up to 1020+ potential system configurations to then return a handful of configurations which best meet design and programmatic criteria.

Multi-objective design of [formula omitted] control charts with fuzzy process parameters using the hybrid epsilon constraint PSO

Control charts are the most useful tools for monitoring production and service processes. Their design involves the selection of such design parameters as sample size, control limits, and sampling frequency. This paper considers the design of X¯ control charts as a multiple objective decision making problem (MODM) which is identified by three criteria: expected hourly cost, in-control average run length, and detection power of control chart. To solve the MODM problem, we propose a hybrid method based on an evolutionary algorithm. In this method, an epsilon constraint is integrated with PSO (particle swarm optimization) as a multi-objective framework. Also, we consider the magnitude of the process shift and the occurrence rate of an assignable cause as fuzzy numbers. Hence, the fuzziness is modeled using both minimax and maximin approaches. Generally, we present a control chart which is suitable for processes with fuzzy parameters and is effective for a range of values of process parameters. A numerical example from the literature is used to illustrate the procedure used for solving the proposed hybrid algorithm.

Multicommodity Flow Model for Multimodal Transportation Planning

This paper presents a methodology for a more efficient way of freight transportation planning through the use of a multimodal network. The freight forwarder can use combinations of non-scheduled truck and scheduled air transportation. This problem attempts to combine the flexible-time service of truck transportation with the scheduled-time service of air transport through Mixed Integer Linear Programming (MILP) that is formulated as a Multi-Commodity Flow Problem. This paper uses the data from an express delivery service network with multiple objective decisions, which are to minimize total transportation cost and transportation time for each commodity. The method used in the research aims to consolidate the freight commodities to minimize the overall transportation costs and to meet time constrained demands.

A multiple objective decision making model for energy generation portfolio under fuzzy uncertainty: Case study of large scale investor-owned utilities in Florida

The objective of this paper is to present a methodology to evaluate the viability of developing solar photovoltaic projects for large investor-owned utilities. By taking into account the trade-off between the cost per kWh of electricity generation and total risk for an investor-owned utility, a multi-objective model of the energy generation portfolios is developed. The decision making model can determine the proportion of different energy generation sources in an investor-owned utility portfolio that reduces risk while providing the lowest cost per kWh of electricity generation possible. In order to measure the risk of the investor-owned utility for energy portfolio selection, an investigation of possible dangers and failures of energy generation portfolios is made and 9 main failure modes are identified. The failure mode and effects analysis is employed to calculate the risk priority numbers for each risk. To deal with the uncertainties of the levelized cost of electricity and risk levels of failure modes, the fuzzy method is introduced and an equivalent crisp model is derived which is then solved by employing a multiple objective particle swarm optimization algorithm. The analysis for four large scale investor-owned utilities in Florida is presented to highlight the performance of the developed optimization method.

The Application of Correlation Dimension in the Multi-Objective Comprehensive Evaluation of the Large Complex Equipment Procurement Scheme

The multi-objectives of procurement scheme evaluation and the complicated nonlinear are pointed out in this paper according to the definition and characteristics of large complex equipments, and with regard to the defects present in the existing multi-objective comprehensive evaluation method, the assessment method of using fractal correlation dimension as the comprehensive quantitative index of multi-objective decision making in the large complex equipment procurement scheme is put forward, and the efficiency of such method is verified by the example of combat aircraft, which provides a new idea for the multiple objective decision making in the large complex equipment procurement scheme.

Long-Term Environmental Research: The Upper Washita River Experimental Watersheds, Oklahoma, USA

Water is central to life and earth processes, connecting physical, biological, chemical, ecological, and economic forces across the landscape. The vast scope of hydrologic sciences requires research efforts worldwide and across a wide range of disciplines. While hydrologic processes and scientific investigations related to sustainable agricultural systems are based on universal principles, research to understand processes and evaluate management practices is often site-specific to achieve a critical mass of expertise and research infrastructure to address spatially, temporally, and ecologically complex systems. In the face of dynamic climate, market, and policy environments, long-term research is required to understand and predict risks and possible outcomes of alternative scenarios. This special section describes the USDA-ARS's long-term research (1961 to present) in the Upper Washita River basin of Oklahoma. Data papers document datasets in detail (weather, hydrology, physiography, land cover, and sediment and nutrient water quality), and associated research papers present analyses based on those data. This living history of research is presented to engage collaborative scientists across institutions and disciplines to further explore complex, interactive processes and systems. Application of scientific understanding to resolve pressing challenges to agriculture while enhancing resilience of linked land and human systems will require complex research approaches. Research areas that this watershed research program continues to address include: resilience to current and future climate pressures; sources, fate, and transport of contaminants at a watershed scale; linked atmospheric-surface-subsurface hydrologic processes; high spatiotemporal resolution analyses of linked hydrologic processes; and multiple-objective decision making across linked farm to watershed scales.

Applying nonlinear MODM model to supply chain management with quantity discount policy under complex fuzzy environment

Purpose: The aim of this paper is to deal with the supply chain management (SCM) with quantity discount policy under the complex fuzzy environment, which is characterized as the bifuzzy variables. By taking into account the strategy and the process of decision making, a bifuzzy nonlinear multiple objective decision making (MODM) model is presented to solve the proposed problem. Design/methodology/approach: The bi-fuzzy variables in the MODM model are transformed into the trapezoidal fuzzy variables by the DMs's degree of optimism α 1 and α 2 , which are de-fuzzified by the expected value index subsequently. For solving the complex nonlinear model, a multi-objective adaptive particle swarm optimization algorithm (MO-APSO) is designed as the solution method. Findings: The proposed model and algorithm are applied to a typical example of SCM problem to illustrate the effectiveness. Based on the sensitivity analysis of the results, the bifuzzy nonlinear MODM SCM model is proved to be sensitive to the possibility level α 1 .

Integration of Building Information Modeling and Economic and Environmental Impact Analysis to Support Sustainable Building Design

AbstractSustainable construction is critical to the architecture-engineering-construction (AEC) industry. The consideration and selection of optimal building components is necessary in order to fulfill multiple objectives of sustainable construction, which are often conflicting. Today, information and communication technologies (ICT) such as building information modeling (BIM) are widely used in the construction industry for decision making during design and construction. However, due to the complexity of building and construction, supporting multiple-objective decision making is not trivial. Currently, BIM has limited capability to support such a process. This paper introduces Simulation of Environmental Impact of Construction (SimulEICon), which is an extension of BIM designed specifically to aid in the decision-making process during the design stage of a construction project. SimulEICon is an add-on to the Autodesk Revit Architecture software, and it uses Microsoft Access for database-related operation...

The study of business performance and multi-objective decision support system for the Taiwan banking industry

Business performance and multi-objective decision support systems play a critical role forsurviving in a strongly competitive global market. Accurate business performance evaluation is akey to strength enterprises competition. In this paper, we collect the financial indices of therelevant literatures for analyzing the relationship among the indices. Four different abilities are commonly considered when analyzing the financial health of a company--liquidity/Debt-paying, financial structure/Stability, activity/efficiency, and profitability. Each one has different indices for measurement. In total, there are 11 indices included (e.g. Current ratio, Quick Ratio, Debt to Total Assets Ratio, Permanent Capital to Fixed Assets Ratio, Accounts Receivable Turnover, Average Accounts Receivable Collection, Fixed Asset Turnover Ratio, Total Asset Turnover Ratio, Return on Assets, Return on Equity, Net Profit Ratio). In order to select better performance indices, we adopt structural equationmodel (SEM) to explore the relationship among the various indicators. Once we find out thecritical indices, we can use them to evaluate business performance. Meanwhile, we develop a multi-objective decision programming model for the Taiwan banking Industry for adequately allocating resources to improve profits. Finally, a multiple objective decision support system is built and the modeling and result of business performance evaluation is presented and some suggestions are given to managers for making decisions.

Applying rough random MODM model to resource-constrained project scheduling problem: A case study of Pubugou Hydropower Project in China

To improve the scheduling efficiency in the Pubugou Hydropower Project, this paper studies the practical resource-constrained project scheduling problem with multi-mode (MRCPSP) in its Construction and Decoration Systems. By taking into account the roughness and randomness in the hybrid uncertain environment, a rough random Multiple Objective Decision Making (MODM) model is presented. To deal with the complex uncertainties, the rough random expected value model is used to obtain an equivalent crisp model. Subsequently, motivated by the particular nature of MODM model, Multiple Objective Particle Swarm Optimization (MOPSO) algorithm is employed to search the Pareto optimal solutions. An practical application to Construction and Decoration Systems in Pubugou Hydropower Project is presented to verify the practicability of the proposed rough random MODM model and the efficiency of the solution algorithm.

Materials Selection Decision Making with Incomplete Information

Material selection is the process of selecting the best possible material for an application from among all the possible alternatives. Both Multiple Objective Decision Making (MODM) and Multiple Attribute Decision Making (MADM) methods can be applied for the selection procedure; however, both the techniques require the availability of complete data which limits the scope of participant materials. Through this study an attempt has been made to do material selection under missing data conditions using technique for order preference by similarity to ideal solution (TOPSIS) approach for four different material sets namely hard coating materials, magnetic materials, piezoelectric materials and micro-electromechanical system (MEMS) materials. It was observed that up-to 10% missing data, the average value of Spearman’s rank correlation coefficient was higher than 0.8. It can be concluded that material selection under missing data can be safely applied to rank novel materials, with unreported properties.

시스템즈 엔지니어링 기법을 이용한 원자력발전소 부지 선정 방법에 대한 연구

Nuclear power plant site selection is a complex process and its successful completion is a critical milestone in the NPP development cycle. Proper siting of NPP will ensure public health and safety, environmental conservation, reduced project failure risks and a smooth NPP development process among other benefits. The objective of this paper is to demonstrate the application of systems engineering to the problem of NPP siting in Kenya. The siting process demonstrated in this paper includes stakeholder need analysis where stakeholders are identified and their needs concerning NPP site are elicited and converted into system functional requirements. A value model is then developed and potential sites iteratively subjected to three types of criteria i.e. exclusionary criteria, avoidance criteria and suitability criteria. This process is used to identify the candidate sites. An additive value model; multiple objectives Decision Analysis (MODA) is then used to calculate candidate solutions values. The site with the highest solution value score is selected. Sensitivity studies using different criterion weight sets (thereby reflecting different viewpoints) can be conducted to assess their effect on the selection of a preferred site and thereby lend additional credibility to the decision process.

Application of Water Resources System Analysis Method in Optimal Allocation of Water Resources

Elaborate the optimal allocation of water resources system connotation, significance and the role of the sustainable utilization of water resources. Based on the water resources system analysis, discusses the system analysis method of water resources and the steps and mathematical model, and the linear programming model for the optimal allocation of water resources in the mathematical model, based on the fuzzy mathematics and the theory of multiple objective decision-making, fuzzy comprehensive evaluation combined with analytic hierarchy process, with the set value statistical and fuzzy membership function of indexes are calculated, determine the evaluation matrix, and then constructs a multi objective comprehensive evaluation model, and using computer to realize the optimal allocation of water resources, to provide a scientific basis.

Multiple Criteria Decision Making Research of Flight Control System Design

Flight control system; multiple criteria decision making; multiple objective decision making; multiple attribute decision making; neural network; mean impact value index. Abstract. It is complex and difficult to tune the parameters of the flight controller. To solve such problem, a multiple objective decision making (MODM) method by using the reference model which is built based on the criteria, is proposed. In order to resolve defects of the multiple attribute decision making (MADM) that the arbitrary of the subjective attribute weights and ignoring the objective message of the objective attribute weights, a subjective attribute weights based on the BP neural network by using the MIV (mean impact value) index is proposed. Finally, a combining method based on the TOPSIS is used to give the final attribute weights. The simulation results show that the method could obtain a set of trade-off solutions which satisfy the requirements of the MODM and could tune the controller effectively.