Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Explicit Building Block Multiobjective Evolutionary Computation: Methods and Applications

This dissertation presents principles, techniques, and performance of evolutionary computation optimization methods. Concentration is on concepts, design formulation, and prescription for multiobjective problem solving and explicit building block (BB) multiobjective evolutionary algorithms (MOEAs). Current state-of-the-art explicit BB MOEAs are addressed in the innovative design, execution, and testing of a new multiobjective explicit BB MOEA. Evolutionary computation concepts examined are algorithm convergence, population diversity and sizing, genotype and phenotype partitioning, archiving, BB concepts, parallel evolutionary algorithm (EA) models, robustness, visualization of evolutionary process, and performance in terms of effectiveness and efficiency. The main result of this research is the development of a more robust algorithm where MOEA concepts are implicitly employed. Testing shows that the new MOEA can be more effective and efficient than previous state-of-the-art explicit BB MOEAs for selected test suite multiobjective optimization problems (MOPs) and U.S. Air Force applications. Other contributions include the extension of explicit BB definitions to clarify the meanings for good single and multiobjective BBs. A new visualization technique is developed for viewing genotype, phenotype, and the evolutionary process in finding Pareto front vectors while tracking the size of the BBs. The visualization technique is the result of a BB tracing mechanism integrated into the new MOEA that enables one to determine the required BB sizes and assign an approximation epistasis level for solving a particular problem. The culmination of this research is explicit BB state-of-the-art MOEA technology based on the MOEA design, BB classifier type assessment, solution evolution visualization, and insight into MOEA test metric validation and usage as applied to test suite, deception, bioinformatics, unmanned vehicle flight pattern, and digital symbol set design MOPs

Water Availability Modeling to Support Water Management in the Lower Rio Grande Valley of Texas

The Rio Grande River is considered as an over-appropriated river basin in Texas, where the number of permits to use surface waters exceed the amount of available water. Agricultural and municipal water supply and use in the Lower Rio Grande Valley (LRGV) are essentially dependent upon storage of the International Amistad and Falcon Reservoirs, which are owned and operated by the International Boundary and Water Commission (IBCW) based on provisions of the 1944 treaty between Mexico and the United States. The Texas share of the waters of the Rio Grande is allocated among numerous farmers, irrigation districts, and cities by a unique water rights permit system administered by the Rio Grande watermaster of the Texas Commission on Environmental Quality (TCEQ). The Rio Grande Water Availability Model (WAM) obtained from the TCEQ WAM System has a hydrologic period-of-analysis of 1940-2000. However, hydrology since 2000 includes the severe 2008-2014 drought and is important to the simulation study. The hydrologic period of analysis for the Rio Grande WAM was extended from 2001 to 2015 using Water Rights Analyses Package (WRAP) programs and methodologies. Extending the hydrologic period-of-analysis of the Rio Grande WAM to cover 1940-2015 was an initial major task in the research. A WRAP/WAM simulation combines natural hydrology represented by sequences of monthly naturalized streamflows and reservoir evaporation-precipitation rates for a specified hydrologic period-of-analysis, 1940-2015 in this study, with specified scenarios of water resources development, allocation, management, and use. Water availability is assessed based on supply reliability metrics and storage and flow frequency metrics computed from simulation results. Additionally, the Rio Grande WAM original 1940-2000 hydrologic period of analysis is extended to cover 1940-2015 and long-term simulations were performed to develop water supply reliability and storage frequency metrics for major water right groups, reallocation of municipal water rights in the Amistad-Falcon Reservoir system, and water planning scenarios including drought management. The Conditional Reliability Modeling (CRM) methods were applied to assess short-term water planning and management strategies for the LRGV along with the drought management scenarios were simulated to predict the likelihood of extended drought conditions based on beginning storage in the Amistad-Falcon Reservoir system. The reliability and exceedance frequencies of maximum end-of-month storage at Amistad and Falcon reservoirs were developed using CRM

Spatially optimised sustainable urban development

PhD ThesisTackling urbanisation and climate change requires more sustainable and resilient cities, which in turn will require planners to develop a portfolio of measures to manage climate risks such as flooding, meet energy and greenhouse gas reduction targets, and prioritise development on brownfield sites to preserve greenspace. However, the policies, strategies and measures put in place to meet such objectives can frequently conflict with each other or deliver unintended consequences, hampering long-term sustainability. For example, the densification of cities in order to reduce transport energy use can increase urban heat island effects and surface water flooding from extreme rainfall events. In order to make coherent decisions in the presence of such complex multi-dimensional spatial conflicts, urban planners require sophisticated planning tools to identify and manage potential trade-offs between the spatial strategies necessary to deliver sustainability. To achieve this aim, this research has developed a multi-objective spatial optimisation framework for the spatial planning of new residential development within cities. The implemented framework develops spatial strategies of required new residential development that minimize conflicts between multiple sustainability objectives as a result of planning policy and climate change related hazards. Five key sustainability objectives have been investigated, namely; (i) minimizing risk from heat waves, (ii) minimizing the risk from flood events, (iii) minimizing travel costs in order to reduce transport emissions, (iv) minimizing urban sprawl and (v) preventing development on existing greenspace. A review identified two optimisation algorithms as suitable for this task. Simulated Annealing (SA) is a traditional optimisation algorithm that uses a probabilistic approach to seek out a global optima by iteratively assessing a wide range of spatial configurations against the objectives under consideration. Gradual ‘cooling’, or reducing the probability of jumping to a different region of the objective space, helps the SA to converge on globally optimal spatial patterns. Genetic Algorithms (GA) evolve successive generations of solutions, by both recombining attributes and randomly mutating previous generations of solutions, to search for and converge towards superior spatial strategies. The framework works towards, and outputs, a series of Pareto-optimal spatial plans that outperform all other plans in at least one objective. This approach allows for a range of best trade-off plans for planners to choose from. ii Both SA and GA were evaluated for an initial case study in Middlesbrough, in the North East of England, and were able to identify strategies which significantly improve upon the local authority’s development plan. For example, the GA approach is able to identify a spatial strategy that reduces the travel to work distance between new development and the central business district by 77.5% whilst nullifying the flood risk to the new development. A comparison of the two optimisation approaches for the Middlesbrough case study revealed that the GA is the more effective approach. The GA is more able to escape local optima and on average outperforms the SA by 56% in in the Pareto fronts discovered whilst discovering double the number of multi-objective Pareto-optimal spatial plans. On the basis of the initial Middlesbrough case study the GA approach was applied to the significantly larger, and more computationally complex, problem of optimising spatial development plans for London in the UK – a total area of 1,572km2. The framework identified optimal strategies in less than 400 generations. The analysis showed, for example, strategies that provide the lowest heat risk (compared to the feasible spatial plans found) can be achieved whilst also using 85% brownfield land to locate new development. The framework was further extended to investigate the impact of different development and density regulations. This enabled the identification of optimised strategies, albeit at lower building density, that completely prevent any increase in urban sprawl whilst also improving the heat risk objective by 60% against a business as usual development strategy. Conversely by restricting development to brownfield the ability of the spatial plan to optimise future heat risk is reduced by 55.6% against the business as usual development strategy. The results of both case studies demonstrate the potential of spatial optimisation to provide planners with optimal spatial plans in the presence of conflicting sustainability objectives. The resulting diagnostic information provides an analytical appreciation of the sensitivity between conflicts and therefore the overall robustness of a plan to uncertainty. With the inclusion of further objectives, and qualitative information unsuitable for this type of analysis, spatial optimization can constitute a powerful decision support tool to help planners to identify spatial development strategies that satisfy multiple sustainability objectives and provide an evidence base for better decision making

Managing Water Resources in Large River Basins

Management of water resources in large rivers basins typically differs in important ways from management in smaller basins. While in smaller basins the focus of water resources management may be on project implementation, irrigation and drainage management, water use efficiency and flood operations; in larger basins, because of the greater complexity and competing interests, there is often a greater need for long-term strategic river basin planning across sectors and jurisdictions, and considering social, environmental, and economic outcomes. This puts a focus on sustainable development, including consumptive water use and non-consumptive water uses, such as inland navigation and hydropower. It also requires the consideration of hard or technical issues—data, modeling, infrastructure—as well as soft issues of governance, including legal frameworks, policies, institutions, and political economy. Rapidly evolving technologies could play a significant role in managing large basins. This Special Issue of Water traverses these hard and soft aspects of managing water resources in large river basins through a series of diverse case studies from across the globe that demonstrate recent advances in both technical and governance innovations in river basin management

IIASA Reports, IIASA Conference '80 - Applied Systems Analysis: From Problem through Research to Use

"IIASA Conference '80," which took place 19-22 May l980, was the second such meeting in the life of the Institute, the first having taken place in l976. Since this meeting occurred during the Institute's eighth year, it celebrated the growing maturity of the research program by centering its attention on the theme "Applied Systems Analysis: From Problem through Research to Use." The Conference included presentations of IIASA's work both in summary and detail; descriptions of IIASA's linkages to other international and national institutions; discussions of uses of IIASA work; and various informal interactions between attendees and members of the IIASA staff. Major technical papers presented include: -- Roger E. Levien, "Applied Systems Analysis: From Problem through Research to Use;" -- Wolf Haefele, "Putting the Results of the IIASA Energy Systems Program to Work;" -- Ferenc Rabar, "Food and Agriculture Systems: Global and National Issues;" -- Andrei Rogers, "Migration, Urbanization, and Development;" -- Murat Albegov, "Regional Development: From Cases to Generalization;" -- Janusz Kindler, "Toward Integrated Policies for Water-Resources Management;" -- Rolfe Tomlinson, "Systems Approaches to Industrial Problems;" -- Andrzej Wierzbicki, "The Challenge of Applied Problems;" and -- Hugh J. Miser, "The Evolving Craft of Systems Analysis.

Expanding Geographic Access to Fertility Care in the United States: A Statistical and Multiobjective Optimization Approach

An estimated 25% of potential demand is met in the US for Assisted Reproductive Technology (ART). ART includes in vitro fertilization, which is one of the most effective ways to treat infertility and is used generally after alternate treatment options have failed. Of the many barriers to accessing ART, geographic barriers can be addressed using operations research methods to develop cost-effective strategies for expanding access. First, a systematic web-search was performed to collect the locations of all main and satellite ART clinics. 13M reproductive-age women were found to lack geographic access to ART. Geographic access to ART was calculated based on race and ethnicity, and 17% fewer American Indians and Alaska Natives were found to have geographic access to ART compared with all US races. Next, explanatory models of geographic access to care were developed, in which the presence of ART clinics in an area was statistically related to female reproductive-age population and median income. Additionally, infertility treatment demand, as measured by the annual number of ART cycles performed in a county, was explored statistically as a function of socioeconomic and environmental health factors. This statistical model predicted values for ART demand for every US county and provided insights into the importance of county characteristics. Population aside, the two most important factors in predicting ART demand were the positively correlated Primary Care Physician Rate and the negatively correlated Severe Housing Cost Burden. Lastly, outputs from the models predicting demand were embedded in a maximal covering location problem (MCLP) mixed integer programming framework to optimize county-level placement of new ART clinics to improve geographic access to ART, as measured by the reproductive-age population covered and predicted demand covered. A novel multiobjective optimization approach was employed in which Pareto-optimal solutions for new clinic locations were compared with existing clinic locations to identify new clinic locations that maximize unmet demand covered vs. maximize unserved population covered. Finally, an ensemble of recommended locations for new clinics was produced by spatially combining the recommendations from statistical and optimization methods, and the concurrence of model recommendations identified Northwest Arkansas/Southwest Missouri to locate a new ART clinic

Water Availability Modeling to Support Water Management in the Lower Rio Grande Valley of Texas

The Rio Grande River is considered as an over-appropriated river basin in Texas, where the number of permits to use surface waters exceed the amount of available water. Agricultural and municipal water supply and use in the Lower Rio Grande Valley (LRGV) are essentially dependent upon storage of the International Amistad and Falcon Reservoirs, which are owned and operated by the International Boundary and Water Commission (IBCW) based on provisions of the 1944 treaty between Mexico and the United States. The Texas share of the waters of the Rio Grande is allocated among numerous farmers, irrigation districts, and cities by a unique water rights permit system administered by the Rio Grande watermaster of the Texas Commission on Environmental Quality (TCEQ). The Rio Grande Water Availability Model (WAM) obtained from the TCEQ WAM System has a hydrologic period-of-analysis of 1940-2000. However, hydrology since 2000 includes the severe 2008-2014 drought and is important to the simulation study. The hydrologic period of analysis for the Rio Grande WAM was extended from 2001 to 2015 using Water Rights Analyses Package (WRAP) programs and methodologies. Extending the hydrologic period-of-analysis of the Rio Grande WAM to cover 1940-2015 was an initial major task in the research. A WRAP/WAM simulation combines natural hydrology represented by sequences of monthly naturalized streamflows and reservoir evaporation-precipitation rates for a specified hydrologic period-of-analysis, 1940-2015 in this study, with specified scenarios of water resources development, allocation, management, and use. Water availability is assessed based on supply reliability metrics and storage and flow frequency metrics computed from simulation results. Additionally, the Rio Grande WAM original 1940-2000 hydrologic period of analysis is extended to cover 1940-2015 and long-term simulations were performed to develop water supply reliability and storage frequency metrics for major water right groups, reallocation of municipal water rights in the Amistad-Falcon Reservoir system, and water planning scenarios including drought management. The Conditional Reliability Modeling (CRM) methods were applied to assess short-term water planning and management strategies for the LRGV along with the drought management scenarios were simulated to predict the likelihood of extended drought conditions based on beginning storage in the Amistad-Falcon Reservoir system. The reliability and exceedance frequencies of maximum end-of-month storage at Amistad and Falcon reservoirs were developed using CRM