Compromise Alternative Research Articles

Voting on the flag of the Weimar Republic

We describe and analyze the voting process leading to the compromise achieved in the Weimar Flag Controversy. We also offer a simple theoretical model that attempts to capture the main forces at work. These forces are: (1) the addition of a compromise alternative that is located between the main ideological positions on the left and on the right; (2) the interdependence of preferences that makes the compromise salient; and (3) a voting process that gradually reveals and aggregates information. Finally, we compare the theoretical insights with the observed outcome.

A hybrid method to solve reliability-cost-oriented bi-objective machine configuration problem for a flow shop system

Machine configuration is a crucial strategic decision in designing a flow shop system (FSS) and directly affects its performance. This involves selecting device suppliers and determining the number of machines to be configured. This study addresses a bi-objective optimization problem for an FSS that considers repair actions and aims to determine the most suitable machine configuration that balances the production reliability and purchase cost. A nondominated sorting genetic algorithm II (NSGA-II) is used to determine all the Pareto solutions. The technique for order preference by similarity to an ideal solution is then used to identify a compromise alternative. It is necessary to assess the production reliability of any machine configuration identified by the NSGA-II. The FSS under the machine configuration is modeled as a multistate flow shop network, and Absorbing Markov Chain and Recursive Sum of Disjoint Products are integrated into the NSGA-II for reliability evaluation. The experimental results of solar cell manufacturing demonstrate the applicability of the proposed hybrid method and validate the efficiency of the NSGA-II compared with an improved strength Pareto evolutionary algorithm.

Compréhension/acceptation de la radiothérapie : un dilemme éthique résolu par une éthique de la considération et de la sollicitude

PurposeEthical questions are poorly investigated specifically in radiation oncology. The objective of the study was to identify and understand the main ethical issue in radiation oncology. Materials and methodsA quantitative analysis was based on the answers to a questionnaire of 200 professionals from 22 radiation oncology departments. The questionnaire mainly aimed to characterize the main ethical issue. A monocentric qualitative analysis was based on semi-structured interviews focused on the main identified ethical issue, carried out with eight technologists, and 20 patients undergoing radiotherapy. ResultsThe main ethical issue was the understanding and/or acceptance of the treatment by the patients (71 %), which frequently arises (more than once a month) (52 %), and corresponds to an ethical tension between the principles of respect for autonomy and beneficence (the good as viewed by the patient) as defined by Beauchamp and Childress. The technologists, wish the patient to be fully involved in his treatment, with the even possibility of refusing it. However, excluding paternalism and autonomic relentlessness, the technologists have the feeling of acting for the good of the patients by treating them with radiation, even if the patients are not always aware of it, because they are within a situation of vulnerability. If the hierarchy of principles is a compromise alternative, this problem is finally well resolved by the effective implementation of an ethic of consideration and solicitude, restoring the patient capabilities, i.e. the maximum development of his potentialities in his situation of vulnerability. Beyond the legal dimension, patient information is crucial and must consider the specific temporality of the patient. ConclusionThe main ethical issue in radiation oncology is the understanding and/or acceptance of the treatment involving the development of an ethic of consideration and solicitude.

Моделювання транспортної логістики військових вантажів з урахуванням збитків, які виникають у зоні бойових дій через запізнення у постачанні

The multi-criteria task related to the simulation of transport logistics for the delivery of military cargo to the war zone in the conditions of delays and risks is stated and solved. The relevance of the study is related to the analysis of possible losses in the war zone (loss of armed forces, damage and destruction of military equipment, change in hostilities from offensive to defensive, etc.) due to the delayed supply of weapons and military equipment. The study simulates the logistics of transportation in the diverse transport networks to ensure timely delivery of military cargo in the conditions of possible delays and risks that affect the amount of damage in the war zone. Given the complex dynamics of military cargo delivery related to heterogeneity and transshipment in the transport network, the original agent simulation model has been created. This model makes it possible to study the supply process and allows to assess delays, risks and losses. A new algorithm to minimize the delivery time of military cargo, based on the distribution of request clones in a graph representing a heterogeneous transport network is presented. An algorithm to minimize supply risks in wartime that considers long logistics chains for transporting military cargo to the war zone is presented. We study the losses caused by the untimely arrival of various types of military equipment and weapons in the war zone, based on full factorial experiments and the assessments of military experts in the field of military logistics are conducted. Given the contradictions of the criteria of delays, risks and losses, the multi-criteria problem of compromise search optimization based on integer (Boolean) programming is stated and solved. The efficiency of the proposed approach is demonstrated by simulating military cargo supply to the war zone. Alternative supply routes, risks and losses due to delays in supply are analyzed. The choice of the compromise alternative of military cargo delivery route to the war zone is substantiated. The scientific novelty of the study is related to the development of methods and models based on agent simulation, experimental theory and integer optimization, that makes it possible to estimate the delays and losses in the supply of military cargo to the war zone in long logistics chains of diverse transport network. The results of the study can be used to build the optimal routes to supply military cargo in wartime.

Constrained Multiobjective Equilibrium Optimizer Algorithm for Solving Combined Economic Emission Dispatch Problem

This research implements a recent evolutionary‐based algorithm of equilibrium optimizer to resolve the constrained combined economic emission dispatch problem. This problem has two objective functions that represent the minimizing of generation costs and minimizing the emission of environmental pollution caused by generators. The proposed algorithm integrates the dominant criteria for multiobjective functions that allow the decision‐maker to detect all the Pareto boundaries of constrained combined economic emission dispatch problem. In order to save the effort for the decision‐maker to select the best compromise alternative, a cluster study was carried out to minimize the size of the Pareto boundary to an acceptable size, representing all the characteristics of the main Pareto frontier. On the other hand, in order to deal with the infringement of constraints, a repair algorithm was used to preserve the viability of the particles. The proposed algorithm is applied to solve the standard 30‐bus IEEE system with 6 generators to validate its robustness and efficiency to produce a well‐distributed Pareto frontier for constrained combined economic emission dispatch problem. Compared with other studies, good results in solving constrained combined economic emission dispatch problem are obtained and a reasonable reduced Pareto set is found.

METHOD OF COMPROMISE CHOICE OF INTERVAL OF MODEL TIME CHANGE IN IMITATION MODEL

The process of simulation is considered as one of the main means for studying the dynamics of functioning of real systems, in particular, complex ones. The system can be represented by a set of components. The functioning of a component is represented by the implementation of a set of functional actions, which are represented by the corresponding activities in the form of a pair: algorithm for performing a functional action - duration of execution. The problem of displaying the simultaneous or parallel nature of the functioning of all components of a complex system in the MI is solved by introducing model or system time. The main methods for introducing model time are the fixed step method and the variable step method. In the fixed-step method, an important problem is the choice of the value of the model time variation interval. The existing recommendations for choosing the value of the interval for changing the model time are of a qualitative nature and their use makes it possible to increase the accuracy of modeling, but at the same time the consumption of the computer time resource increases. It is proposed to use quantitative estimates of the values of quality criteria - the accuracy and expenditure of the computer time resource when choosing the value of the model time change interval. The generalized criterion is represented as a weighted sum of transformations of local criteria. The values of the coefficients by which the corresponding transformations are multiplied express the preferences of the decision-maker for the local optimality criteria. A geometric interpretation of the process of determining a compromise alternative on a set of effective alternatives for various cases of the importance of local criteria is given. These estimates make it possible to substantiate the nature of the change in the quality criteria for various variants of the values of the interval of change in the model time and to use them to select a compromise option among the effective ones by minimizing the generalized criterion. The choice of the compromise value of the model time variation interval is implemented in the control simulation program.

Statistical downscaling or bias adjustment? A case study involving implausible climate change projections of precipitation in Malawi

Statistical downscaling (SD) and bias adjustment (BA) methods are routinely used to produce regional to local climate change projections from coarse global model outputs. The suitability of these techniques depends on the particular application of interest and, especially, on the required spatial resolution. Whereas SD is appropriate for local (e.g., gauge) resolution, BA may be a good alternative when the gap between the predictor and predictand resolution is small. However, the different sources of uncertainty affecting SD such as reanalysis uncertainty, the choice of suitable predictors, climate model, and/or statistical approach may yield implausible projections in particular situations for which BA techniques may offer a compromise alternative, even for local resolution. In this work, we consider a case study with 41 rain gauges over Malawi and show that, despite producing similar results for a historical period, the use of different predictors may lead to large differences in the future projections obtained from SD methods. For instance, using temperature T (specific humidity Q) produces much drier (wetter) conditions than those projected by the raw global models for the target area. We demonstrate that this can be partially alleviated by substituting T+Q by relative humidity R, which simultaneously accounts for both water availability and temperature, and yields regional projections more compatible with the global one. Nevertheless, large local differences still persist, lacking a physical interpretation. In these situations, the use of simpler approaches such as empirical BA may lead to more plausible (i.e., more consistent with the global model) projections.

A Novel Pythagorean Fuzzy LINMAP-Based Compromising Approach for Multiple Criteria Group Decision-Making with Preference Over Alternatives

This paper presents a new compromising approach to multiple criteria group decision-making (MCGDM) for the treatment of uncertainty which is based on Pythagorean fuzzy (PF) sets. The present work intends to propose a novel linear programming technique for multidimensional analysis of preference (LINMAP) by way of some useful concepts related to PF dominance relations, individual consistency and inconsistency levels, and individual fit measurements. The concept of PF scalar function-based dominance measures is defined to conduct intracriterion comparisons concerning uncertain evaluation information based on Pythagorean fuzziness; moreover, several valuable properties are also investigated to demonstrate its effectiveness. For the assessment of overall dominance of alternatives, this paper provides a synthetic index, named a comprehensive dominance measure, which is the aggregation of the weighted dominance measures by combining unknown weight information and PF dominance measures of various criteria. For each decision-maker, this paper employs the proposed measures to evaluate the individual levels of rank consistency and rank inconsistency regarding the obtained overall dominance relations and the decision-maker’s preference comparisons over paired alternatives. In the framework of individual fit measurements, this paper constructs bi-objective mathematical programming models and then provides their corresponding parametric linear programming models for generating the best compromise alternative. Realistic applications with some comparative analyses concerning railway project investment are implemented to demonstrate the appropriateness and usefulness of the proposed methodology in addressing actual MCGDM problems.

Optimization of the production plan by three-criterion modeling

The object of research is the processes of optimizing the production plan according to certain criteria by modeling. One of the most problematic places is the complexity of coordination and taking into account the influence of criteria on the optimal production plan. From the point of view of mathematics, the search for the optimal result can be obtained with different criteria laid down, but from an economic point of view it is important to choose those that are of decisive importance. That is, their weight is important for the consumer in deciding on a purchase and for the manufacturer – in terms of the production capabilities of certain types of products and performance (production efficiency). This problem was solved by solving the three-criterion problem of planning production. The search for a compromise alternative was achieved through a step-by-step solution of the proposed mathematical model for optimizing the production plan according to the most important criteria for the producer and consumer: profit, quality and demand for products of each type, taking into account the known number of units of each resource.The ideal point method, the simplex method and the Lagrange multiplier method are used. The test example provides an algorithm for solving the optimization problem. The result obtained – the three-criterion task of production planning has been solved, which makes it possible to maximize profit from production, product quality and demand for products with known initial resource components. The importance/significance of the developed scientific and methodological approach is confirmed/argued by the fact that the achievement of effective results of the enterprise’s activity directly depends on the optimal production plan.Given the results of the conducted research, out of the many possible alternatives, the enterprise will be able to most efficiently produce the products necessary for the consumer by type and quality. That is, with known resource parameters, the maximum possible positive result is achieved for the manufacturer and for the consumer.The proposed economic and mathematical tools can be used in solving problems of optimizing production in various sectors of the economy.

Men and the Middle: Gender Differences in Dyadic Compromise Effects

Individual decision makers show robust tendencies toward choosing compromise options. But what happens when consumers make choices with someone else? This article examines the choice of compromise options in joint dyadic decisions. Findings reveal that preferences for compromise alternatives replicate in mixed-gender and female-female dyads as among individuals but are attenuated when two males make a choice together. Moreover, when two males make joint choices, their tendency to choose the compromise alternative decreases not only relative to other types of pairs but also to male and female individual decision makers. Evidence is presented that this happens because male-male dyadic contexts cue gender dichotomization, behavior that is consistent with masculine but not feminine gender norms. Because the extremity in decision making is maximally consistent with masculine but not feminine gender role norms, male-male dyads exhibit lower preferences for compromise options. However, if men have an opportunity to signal masculinity to one another prior to making joint compromise choices, male-male dyads prefer compromise options at proportions no different from female-female dyads. This work brings together the judgment and decision-making literature with insights from the social psychology literature, identifying a case when gender role norms have profound influences on classic judgment and decision-making effects.

Compromise solutions in mining method selection - case study in colombian coal mining

The purpose of this paper is to present a quantitative approach to the selection of the mining extraction method by developing a methodological problem of discrete multicriteria decision making (MCDM), this approach seeks to support the process of planning and mine design. Select the extractive method is one of the problems of Discrete Multicriteria Decision (MCDM) where decision-makers had problems in assigning weight to each criterion. To solve this problem, this article suggests the ENTROPY method. This paper wants to handle the subjectivity inherent to this problem by using the VIKOR method, which yields results in a compromise alternative. The methodology proposed in this article applies in coal deposit located in the western side of Cerro Tasajero in Norte de Santander, Colombia

An interval type-2 fuzzy LINMAP method with approximate ideal solutions for multiple criteria decision analysis

The purpose of this paper is to develop a linear programming technique for multidimensional analysis of preference (LINMAP) to address multiple criteria decision analysis problems within the interval type-2 fuzzy environment based on interval type-2 trapezoidal fuzzy numbers. Considering the issue of anchor dependency, we use multiple anchor points in the decision-making process and employ approximate positive-ideal and negative-ideal solutions as the points of reference. Selected useful properties of the approximate ideal solutions are also investigated. In contrast to the classical LINMAP methods, this paper directly generates approximate ideal solutions from the characteristics of all alternatives. Next, this work presents the concept of closeness-based indices using Minkowski distances with approximate ideal solutions to develop a new approach for determining measurements of consistency and inconsistency. Under incomplete preference information on paired comparisons of the alternatives, this paper provides a novel method that uses the concept of comprehensive closeness-based indices to measure the poorness of fit and the goodness of fit. By applying the consistency indices and inconsistency indices, this work formulates an optimization problem that can be solved for the optimal weights of the criteria and thus acquires the best compromise alternative. Additionally, this paper explores the problem of supplier selection and conducts a comparative discussion to validate the effectiveness and applicability of the proposed interval type-2 fuzzy LINMAP method with approximate ideal solutions. Furthermore, the proposed method is applied to address a marketplace decision difficulty (MPDD)-prone decision-making problem to provide additional contributions for practical implications.

An empirical comparison of travel choice models that capture preferences for compromise alternatives

Compromise alternatives have an intermediate performance on each or most attributes rather than having a poor performance on some attributes and a strong performance on others. The relative popularity of compromise alternatives among decision-makers has been convincingly established in a wide range of decision contexts, while being largely ignored in travel behavior research. We discuss three (travel) choice models that capture a potential preference for compromise alternatives. One approach, which is introduced in this paper, involves the construction of a so-called compromise variable which indicates to what extent (i.e., on how many attributes) a given alternative is a compromise alternative in its choice set. Another approach consists of the recently introduced random regret-model form, where the popularity of compromise alternatives emerges endogenously from the regret minimization-based decision rule. A third approach consists of the contextual concavity model, which is known for favoring compromise alternatives by means of a locally concave utility function. Estimation results on a stated route choice dataset show that, in terms of model fit and predictive ability, the contextual concavity and random regret models appear to perform better than the model that contains an added compromise variable.

Ecological functionality of landscapes with alternative rehabilitations of depleted aggregate sites

To explore the implications of surrounding landscape context on the ecological effects of rehabilitation, we assessed three alternative ways of rehabilitating depleted Ontario sites with measures of habitat patterns and cumulative costs (landscape resistance). Alternative rehabilitations focused on (a) economics, (b) biodiversity protection and (c) a compromise of economics and biodiversity. We measured the landscape effects of the different rehabilitations within a 10 km radius of several depleted aggregate sites. A cost-surface model showed that the biodiversity protection alternative achieved lower landscape resistance than the other alternatives, and importantly that this effect could extend well beyond the site. Measuring four attributes of landscape pattern the differences among alternatives showed that the biodiversity alternative offered the best habitat patterns over the economic alternative. Yet for some sites a compromise alternative could achieve similar ecological consequences while balancing competing interests. Broad inclusion of nearby landscape context when designing rehabilitation can substantially affect the ecological outcomes of rehabilitation, and the effects can be quite extensive.

Visualization-based multi-objective improvement of environmental decision-making using linearization of response surfaces

This study presents a new interactive procedure for supporting Decision Makers (DMs) in environmental planning problems involving large, process-based, dynamic models and many (more than two) conflicting objectives. Because of such features of the model, computationally-onerous simulations are the only feasible way of analysis, while the multi-objective nature of the problem entails the combined use of optimization techniques and appropriate tools for the visualization of the associated Pareto frontier. The procedure proposed is based on the iterative improvement of the current best compromise alternative based on interactions with the DM. At each iteration, the DM is informed about the Pareto frontier of a local multi-objective optimization problem, which is generated by linearizing the response surfaces that describe the objectives and constraints of the original planning problem. Interactive visualization of the multi-dimensional Pareto frontier is used to support the DM in choosing the new best compromise alternative. The procedure terminates when the DM is fully satisfied with the current best compromise alternative. The approach is demonstrated in Googong Reservoir (Australia), which is periodically affected by high concentrations of Manganese and Cyanobacteria. Results indicate that substantial improvements could be observed by simply changing the location of the two mixers installed in 2007 and adding another pair of mixers.

Fuzzy Multicriteria Decision Aid Method for Conceptual Design

A general fuzzy multicriteria decision aid method for conceptual design is proposed. It is used for selecting the best compromise alternative, among a finite set of design concepts, considering environmental and economic performance. At the conceptual design phase most of the environmental impact is committed, whereas at that stage the design concepts are imprecisely defined and should be selected based on multiple, often conflicting criteria. Three vacuum cleaners, using different design principles for the dust storage, are analyzed. The best compromise design alternative is selected, considering trade offs between end-of-life profit and environmental criteria.

Strategy-proofness, Pareto optimality and strictly convex norms

A voting scheme assigns to each profile of alternatives chosen by n individuals a compromise alternative. Here the set of alternatives is represented by the Euclidean plane. The individual utilities for the compromise point are equal to the negatives of the distances of this point to the individually best points. These distances are measured by a given strictly convex norm, common to all agents. A voting scheme is strategy-proof, if voting for one’s best point is an optimal strategy for all agents. A characterization is given of all strategy-proof, Pareto optimal voting schemes. Since the Euclidean norm is strictly convex, this result holds for Euclidean preferences in particular.

Fuzzy decision making through trade-off analysis between criteria

In this paper, we propose a new approach in performing trade-off analysis between multiple criteria, called criteria trade-off analysis (CTA). Conflicting degree and cooperative degree between any two criteria are first formulated. Relationships between criteria are identified based upon their conflicting and cooperative degrees. Criteria are converted into their disjunctive normal form to obtain a uniform representation of the criteria, and then arranged into a four-level hierarchical aggregation structure. A set of parameterized aggregation operator, fuzzy and / or, is selected to aggregate the judgements for the alternatives. A compromise alternative, which is proved to satisfy pareto optimality, can thus be obtained through the aggregation of judgements based on the aggregation hierarchical structure.

Voting by veto and the role of the compromise function

This paper analyzes voting by veto procedures in the context of a pure sharing problem. It is shown that the direct intuition about these voting mechanisms fails: the veto power of the players does not by itself make players act in an equitable manner. If the compromise function yields a constant compromise alternative, then it plays the role of a threat point and the behavior of the players in making proposals tends to be selfish. However, if it depends on the individual proposals, and selects a real compromise among them, then egalitarian proposals can be achieved as the unique subgame perfect equilibria with symmetric proposals of the game.

Range convexity, continuity, and strategy-proofness of voting schemes

A voting scheme assigns to each profile of alternatives reported byn individuals a compromise alternative. A voting scheme is strategy-proof if no individual is better off by lying, i.e., not reporting a best alternative. In this paper the main results concern the case where the set of alternatives is the Euclidean plane and the preferences are Euclidean. It is shown that for strategy-proof voting schemes continuity is equivalent to convexity of the range of the voting scheme. Using a result by Kim and Roush (1984), this leads to characterizations of surjective or unanimous, anonymous, strategy-proof voting schemes.