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Nowadays in Supply Chain (SC) networks, a high level of risk comes from SC partners. An effective risk management process becomes as a consequence mandatory, especially at the tactical planning level. The aim of this article is to present a risk-oriented integrated procurement–production approach for tactical planning in a multi-echelon SC network involving multiple suppliers, multiple parallel manufacturing plants, multiple subcontractors and several customers. An originality of the work is to combine an analytical model allowing to build feasible scenarios and a multi-criteria approach for assessing these scenarios. The literature has mainly addressed the problem through cost or profit-based optimisation and seldom considers more qualitative yet important criteria linked to risk, like trust in the supplier, flexibility or resilience. Unlike the traditional approaches, we present a method evaluating each possible supply scenario through performance-based and risk-based decision criteria, involving both qualitative and quantitative factors, in order to clearly separate the performance of a scenario and the risk taken if it is adopted. Since the decision-maker often cannot provide crisp values for some critical data, fuzzy sets theory is suggested in order to model vague information based on subjective expertise. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution is used to determine both the performance and risk measures correlated to each possible tactical plan. The applicability and tractability of the proposed approach is shown on an illustrative example and a sensitivity analysis is performed to investigate the influence of criteria weights on the selection of the procurement–production plan. [ABSTRACT FROM PUBLISHER]

This paper presents the reliability analysis on the basis of the foundation failure against bearing capacity using the concept of fuzzy set theory. A surface strip footing is considered for the analysis and the bearing capacity is estimated using the conventional Finite Element Method (FEM). The spatial variability of the variables is taken into consideration to capture the physical randomness of the soil parameters for an isotropic field. A variation of the probability of failure (Pf) against a varying limiting applied pressure (q) is presented for different Coefficient of Variation (COV) of the variables and different scale of fluctuation (θ). The results reveal that the friction angle of soil (ϕ) is the most influencing parameter among the other variables. Further, the influence of the scale of fluctuation (θ) on the probability of failure (Pf) is also examined. It is observed that for a particular COV of ϕ, higher value of θ predicts higher Pf whereas, Pf increases as COV of ϕ increases for a particular θ value. Later, a comparison study is accomplished to verify the viability of the present method and it can be noticed that the present method compares well with the other reliability method (First Order Reliability Method) to a reasonably good extent. [ABSTRACT FROM AUTHOR]

The aim of this work is to introduce a new category of Fuzzy d-algebra called Γ-Fuzzy d-algebra. This notion is more useful than Fuzzy d-algebra because in the old case the degree of membership of any in the Fuzzy set does not depend on the structure of d-algebra X. Therefore, in this work, we introduced a new construction of Fuzzy d-algebra that is depended on structure of d-algebra. Also, we show that for any d-algebra there is a Γ-Fuzzy d-algebra. Further, this new construction helps us to find the interesting relation between Γ-Fuzzy d-algebra and edge d-algebra in this work. For any d-algebra, we determined unique Γ-Fuzzy topological space using Γ-Fuzzy d-algebra. For any , a new class of d-algebra is introduced, where is the set of all equivalence classes . Finally, a new class of intuitionistic fuzzy set is called intuitionistic Γ-Fuzzy d-algebra is investigated and discussed. [ABSTRACT FROM AUTHOR]

This study proposes an integrated model for capacity planning in electricity generation. It utilizes a multiple-criteria linear programming to incorporate cost and environmental objectives into the planning. To treat the uncertainties embedded in definition of model parameters, the concept of decision-maker degree of optimism will be used. Optimization of the model provides different planning scenarios. To determine the best compromise plan, a post-optimization assessment based on fuzzy set theory concepts is developed. The proposed methodology is employed for a medium-term capacity planning in Canada's electricity generation sector. The results approve a major capacity growth for natural gas facilities accompanied by retirement of most coal-burning facilities. [ABSTRACT FROM AUTHOR]

In real-world situations, the project managers must handle conflicting goals that govern the use of the resources within organizations. These conflicting goals must are required to be optimized simultaneously by the project managers in the framework of fuzzy aspiration levels. The multiple fuzzy goals programming model proposed herein helps project managers to minimize project total costs, total completion time, and total crashing costs considering direct costs, indirect costs, contractual penalty costs, duration of activities and total budget constraint. A numerical example illustrates the feasibility of applying the proposed model to a project management decision problem. Consequently, the proposed model yields an efficient compromise solution and the decision maker's overall degree of satisfaction with determined multiple fuzzy goals values. Moreover, the proposed model effectively provides a systematic decision-making framework, enabling a decision maker to interactively modify the fuzzy data and model parameters until a satisfactory solution is obtained. The significant characteristics that differentiate the proposed model from the other models include flexible decision-making processes, multiple objective functions, and wide-ranging decision information. [ABSTRACT FROM AUTHOR]

Risk analysis in construction is becoming more popular as competition, project size and complexity Increase. Traditional risk analysis relies on rules of thumb. While this approach can work, it is neither robust nor reliable. The development of information technology has made the use of probabilistic estimating and simulation a practicable alternative. These techniques are, however, precise but not necessarily accurate as simplification and many assumptions are used. Further information technology development in expert systems and the paradigm shift in systems engineering from a hard to soft approach has promoted an alternative approach to risk analysis utilizing the theory of frizzy sets which translates linguistic expressions (such as highly likely) into numerical membership functions. This paper introduces risk analysis in construction against characteristics of the industry. It is argued that normative theories in probability are not as applicable in the construction industry as first perceived. The concept of fuzzy sets is described and the difference in approach in modelling risk between probabilistic and fuzzy methods will be presented. Initial empirical study reveals the applicability of frizzy sets theory in risk analysis. This is important in that a model of risk analysis can be developed requiring the user to express risk attitude linguistically. Moreover, the results are also in linguistic terms and can, therefore, be understood and interpreted correctly by the user. [ABSTRACT FROM AUTHOR]

A new approach, based on the theory of fuzzy sets and systems, was proposed to assess the acceptability of stresses involved in manual lifting tasks. Nine male subjects participated in a laboratory lifting experiment. A total of 108 data points (9 subjects × 4 levels of frequency × 3 replications) were collected. The maximum acceptable weights of lift were determined using the psychophysical methodology. Metabolic energy expenditure and heart rates were also measured. A hypothesis, stating that the combined effect of biomechanical and physiological stresses leads to an overall measure of lifting task acceptability as expressed by the psychophysical stress, was suggested and evaluated. Conditions were found for which the acceptability measures of the combined and the psychophysical stresses were close to one another. A concept of safety index for a particular weight of load lifted was also proposed. [ABSTRACT FROM PUBLISHER]

The allocation of human resources is considered as one of daily challenges of many organizations to achieve optimal efficiency. After investigating this challenge, in this research, a multi-agent system is used to make a cooperative game between organizational units for allocation of tasks and human resources in an organization. In the game, every unit provides a proposal for promoting his and other unit's performance. Our model uses fuzzification to facilitate game process and increase probability of reaching an agreement in the game. Meanwhile it helps for simulation of real conditions in organizations. Results of the fuzzy game have shown that for special allocations of human resources and tasks, organizational performance is more desirable, and its productivity will be higher. We used an example to apply the model and show the results. The model can improve the human resources and task allocation in organizations by using a fuzzy game theory. [ABSTRACT FROM AUTHOR]