Compromise solutions for stochastic multicriteria acceptability analysis with uncertain preferences and nonmonotonic criteria

Purpose The decisions taken today relating to urban renewal interventions are rarely supported by logical and operational methodologies capable of effectively rationalising selection processes. For this purpose, it is necessary to propose and implement analysis models with the aim of promoting the sustainable development of the territory. The purpose of this paper is to define a model for the optimal allocation of scarce resources. Design/methodology/approach The Discrete Linear Programming (DLP) is used for selecting investments aimed at achieving financial, social, cultural and environmental sustainability. Findings The proposed model lends itself to the construction of investment plans on behalf of both types of decision makers, of both a public and a private nature. Research limitations/implications All projects are evaluated according to multi-criteria logics, so that it is possible to find compromise solutions, in accordance with the stakeholders’ different preferences. Practical implications The model, written with A Mathematical Programming Language using DLP logics, is tested – case study – so as to define an investment programme finalised for urban renewal of a vast area. Social implications The proposed econometric model makes it possible to obtain the optimal combination of projects for urban renewal with a view to achieving the sustainable development of the territory. Originality/value Using the proposed model, all projects are evaluated according to multi-criteria logics, so that it is possible to find compromise solutions, in accordance with the stakeholders’ different preferences.

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Composition and Analysis of Pareto Optimal Compromise Solutions for Multiobjective Robust Controller Using GPC and CAN2s

Communications in Computer and Information Science - Neural Information Processing ◽

10.1007/978-3-030-63823-8_81 ◽

2020 ◽

pp. 713-722

Author(s):

Hironobu Nakayama ◽

Ko Ogi ◽

Kazuya Matsuo ◽

Shuichi Kurogi

Keyword(s):

Pareto Optimal ◽

Robust Controller ◽

Compromise Solutions

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Methodology of the Polyoptimization for Spatial Processes

Proccedings of 10th International Conference "Environmental Engineering" ◽

10.3846/enviro.2017.100 ◽

2017 ◽

Author(s):

Andrzej Biłozor ◽

Małgorzata Renigier-Biłozor

Keyword(s):

Decision Making ◽

Land Use ◽

Urban Areas ◽

General Rule ◽

Decision Making Process ◽

Spatial Processes ◽

Complex Activity ◽

Compromise Solutions ◽

Gis Tools ◽

Selection Of

Optimization is a complex activity that aims to find the best solution for a given activity, considering all existing limitations. The best variant possible in the set of acceptable variants is sought-out. In particular, in urban areas, optimization of land use function as the beginning of a decision-making process requires performing a great number of tasks, which minimize the risk of spatial conflicts, set at the stage of studies and analyses. Polyoptimization is optimization with a vector objective function. The aim of polyoptimization is to find the best solution, concurrently applying several criteria which, due to their limitations, are conflicting as a general rule. It leads to finding compromise solutions (polyoptimum variants in the set of acceptable variants). In the paper the following ideas will be presented – the idea of spatial processes polyoptimization, the methods for determining the collection and selection of compromise solutions, the methodology for determining polioptimum states of the space use, the possibility of using polyoptimization methods that are regarded as supporting decision-making tools in the planning and management of space with the use of GIS tools. The Authors will show the benefits of using the polyoptimization. The methods of formulating and solving problems which are related to selection of optimum way use of land will be delivered.

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Campaigns, Competition, and Support for Political Compromise

Compromise in an Age of Party Polarization ◽

10.1093/oso/9780197510490.003.0006 ◽

2020 ◽

pp. 103-126

Author(s):

Jennifer Wolak

Keyword(s):

Experimental Data ◽

Survey Data ◽

Policy Outcomes ◽

Compromise Solutions ◽

Campaign Ads ◽

Political Compromise

Campaigns draw people into the partisan practice of politics, through close competition, campaign ads, and calls to take sides. Yet the conflicts of contentious campaigns may do little to encourage compromise, instead leading voters to call on their representatives to deliver on their campaign promises. This chapter shows rather than close the door to compromise, conflicts instead serve as a reminder that other people want different things than we do in politics, disrupting people’s tendencies to assume most others agree with them. Analysis of survey data shows that people who live in states marked by close partisan divides are more likely to prefer a president who is willing to consider compromise. Experimental data confirm that when people learn that other Americans want different policy outcomes, they become more willing to consider compromise solutions.

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The optimization of accuracy and efficiency for multistage precision grinding process with an improved particle swarm optimization algorithm

International Journal of Advanced Robotic Systems ◽

10.1177/1729881419893508 ◽

2020 ◽

Vol 17 (1) ◽

pp. 172988141989350

Author(s):

Zhanying Chen ◽

Xuekun Li ◽

Zongyu Zhu ◽

Zeming Zhao ◽

Liping Wang ◽

...

Keyword(s):

Particle Swarm Optimization ◽

Particle Swarm ◽

Surface Model ◽

Grinding Process ◽

Swarm Optimization ◽

Improved Particle Swarm Optimization ◽

Compromise Solutions ◽

Grinding Parameters ◽

Validation Experiment ◽

Grinding Efficiency

For metal rolling, the quality of final rolled productions (for instance, metal sheets and metal foils) is affected by steel roll’s cylindricity. In roll grinding process, grinding parameters, which typically involve multiple substages, determine the steel roll’s quality and the grinding efficiency. In this article, a modified particle swarm optimization was presented to dispose of roll grinding multi-objective optimization. The minimization of steel roll’s cylindrical error and maximization of grinding efficiency were optimization objectives. To build the correlation between grinding parameters and cylindrical error, the response surface model of cylindrical error was regressed from the operation data of machine tool. The improved particle swarm optimization was employed to the roll grinding parameter optimization, and the optimal compromise solutions between grinding efficiency and cylindrical error were obtained. Based on the optimal compromise solutions, engineers or computer were capable to determine the corresponding most efficient roll grinding parameters according to the requirement of the final cylindrical error specification. To validate the efficacy of the improved particle swarm optimization, the validation experiment was carried out on the practical roll grinding operation. The error between the calculated optimized cylindrical error and experimental cylindrical error is less than 7.73%.

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