2024 Robust possibilistic programming

Robust possibilistic programming

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August undefined, 2024

In this paper, the goal is to determine optimal order quantity and backordering size for each product. To develop a realistic mathematical model of the problem, three robust possibilistic programming (RPP) approaches are developed to deal with uncertainty in main parameters of the model. See more As mentioned earlier, in this research several algorithms were utilized to solve the proposed robust formulation of the problem. For this purpose, several numerical … See more In this study, two main measures are considered to compare the performance of the two algorithms. The first one is CPU-time measure and the second one is … See more To evaluate the difficulty of solving the robust model, a schematic view of the computation time of the algorithms is presented in Fig. 12. In Fig. 12, the vertical axis … See more WebThe robust possibilistic programming (RPP) approach is used to cope with the uncertainty. In this paper, the realistic and the hard worst-case robust approaches are used. The realistic and the soft worst-case robust models became the same because we are only concerned about the robustness of the makespan. Comparing the results between fuzzy and ...

Multi-objective closed-loop supply chain network design: A novel robust …

WebFirst, the steps of the TH method are as follows: Step 1: Determine the distribution of each fuzzy parameter with the most pessimistic, the most possible, and the most... Step 2: … hoyne bank wheeling il

Blood supply chain network design considering blood group compatibility …

WebSep 14, 2024 · Due to the presence of the uncertainty in the problem’s parameters, the possibilistic programing approach which is a subset of fuzzy programing has been used. The proposed model has been... WebJul 29, 2024 · A possibilistic programming model and simulation-based solution method are developed for organ transplant center location, allocation, and distribution. The proposed mathematical model optimizes the overall cost by considering the fuzzy uncertainty of organ demands and transportation time. WebTo cope with the uncertainty, a robust programming approach was extended into flexible-possibilistic programming. The final model controls the uncertainty and risk-aversion of output decisions and effectively confronts the adverse effects of disruptions. hoy nba playoff

Robust possibilistic programming for socially responsible supply …

Robust Programming - UC Davis

WebOct 1, 2024 · Several robust fuzzy data envelopment analysis (RFDEA) models are proposed by the use of different fuzzy measures including possibility, necessity and credibility measures to produce both conservative and non-conservative methods based on various fuzzy measures. Possibilistic programming approach is one of the most popular methods … WebSep 16, 2024 · A robust possibilistic programming approach is developed to optimize the routing problem by obtaining its robust solutions. A case study is presented to demonstrate the feasibility of the proposed approaches. hoyne brewing companyWebA robust possibilistic programming approach is developed to optimize the routing problem by obtaining its robust solutions. A case study is presented to demonstrate the feasibility hoyne chicago il

"WebOct 1, 2024 · In this paper, the goal is to determine optimal order quantity and backordering size for each product. To develop a realistic mathematical model of the problem, three robust possibilistic programming (RPP) approaches are developed to deal with uncertainty in main parameters of the model. " - Robust possibilistic programming

Robust possibilistic programming

Robust Platelet Logistics Planning in Disaster Relief ... - Springer

WebDec 1, 2024 · Zadeh (1978) was the pioneer researcher in possibilistic programming that proposed the fundamental principles of possibility theory and then many studies have been done to extend the possibility theory. He propounded that the possibility theory is a mathematical theory to model certain types of uncertainty as an alternative for probability … WebNov 1, 2012 · To this aim, first a bi-objective mathematical programming model is developed wherein its objective functions include minimizing the total cost and maximizing the …

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WebRobust Programming. Matt Bishop. Department of Computer Science University of California at Davis Davis, CA 95616-8562. Introduction. Robust programming, also called … WebA Possibilistic Programming Approach to Portfolio Optimization Problem under Fuzzy Data - A Robust Variant of Radial Measure for Performance …

WebMay 12, 2024 · In order to embed the uncertainty of transportation costs, blood demand, capacity of facilities and carbon emission, a novel robust possibilistic-necessity optimization used regarding a hybrid... WebAs fuzzy mathematical programming is categorized into Possibilistic programming and Flexible programming, ROFP also can be classified into: [2] Robust possibilistic …

WebAfter that, a robust possibilistic programming (RPP) model of the proposed problem is introduced to deal with the uncertainty of the model’s parameters. While the applicability of the proposed models is addressed, it is revealed that the RPP model obtains better solutions in comparison with the BPCCP model for different realizations and ... WebProposing an interactive flexible robust possibilistic programming technique that significantly benefits from both flexible programming and robust programming and provides robust strategic and tactical-level decisions under multiple uncertainties.

WebMay 1, 2024 · Robust possibilistic programming for socially responsible supply chain network design: A new approach Fuzzy Sets and Systems (2012) A.L. Medaglia et al. A multiobjective evolutionary approach for linearly constrained project selection under uncertainty European Journal of Operational Research (2007) J.M. Laínez et al.

http://nob.cs.ucdavis.edu/classes/ecs153-2005-02/handouts/robust.pdf hoyne chiropracticWebAnother contribution of this research is the development of a basic possibilistic chance-constrained programming (BPCCP) approach. After that, a robust possibilistic … hoyne field loyolaWebApr 14, 2024 · A robust possibilistic programming approach is applied to address the uncertainties. A fully-decentralized approach called the alternating direction method of multipliers (ADMM) is utilized to solve the presented decentralized robust problem. hoyne parkWebAug 1, 2014 · Possibilistic programming is used to address imprecise/ambiguous parameters of objective functions and constraints that are modeled by utilizing available objective data that are not enough in... hoy neresiWebDec 1, 2024 · To deal with uncertainty, the robust optimization approach is employed in order to maximize the profit earned from the bioethanol sales at the foreign/domestic markets, minimize the environmental... hoyne for sheriffWebFeb 21, 2024 · A multi-objective robust possibilistic programming approach to sustainable switchgrass-based bioethanol supply chain network design Journal of cleaner production April 1, 2024 See publication hoyne chiropractic maryboroughWebRobust Programming Matt Bishop 1 Department of Computer Science University of California at Davis Davis, CA 95616-8562 Introduction Robust programming, also called … hoyne field