Aquila Optimizer: A novel meta-heuristic optimization algorithm

Introduction to quality engineering : designing quality into products and processes

Contents: Variety and Quality. Variability loss and tolerance. Determining tolerances. Tolerance design and experimental design. Offline and online quality control. Parameter design and tolerance design: case study. Experimental design for smaller is better characteristics. Experimental design for larger is better characteristics. Bypassing the S/N ratio: spring experiment. Experimental design for dynamic characteristics.

Introduction to quality engineering. designing quality into products a

Henry gas solubility optimization: A novel physics-based algorithm

After the first paper regarding the Best Worst Method (BWM) was published in Omega in 2015 (J. Rezaei, Best-worst multi-criteria decision-making method, Omega 53 (2015) 49–57), it has attracted many scholars’ attention due to the efficiency of this method in reducing the times of pairwise comparisons and the good performance in maintaining consistency between judgments. Lots of researches related to this method have been published over the past several years. This paper concentrates on the state-of-the-art survey of the BWM based on the in-depth analysis over the publications concerning this method published from 2015 to 26th, January 2019. This paper intends to answer five questions about the BWM: (1) How does this method perform in bibliometric analysis? (2) Why to propose this method and what is it? (3) Which integrations that the BWM were focused on and which areas did they apply to? (4) What extensions of this method were investigated? (5) What are the challenges and future research directions regarding this method? In view of the fact that the research on this method is still in infancy, this paper has guiding significance for the later research related to the BWM. From the theoretical point of view, the reasonable value of consistency ratio, the inconsistency improving methods, the uncertain extensions of the BWM and the techniques for solving multi-optimality model in the BWM are good research issues that need to be further investigated in the future. From the perspective of application, the software packages for this method, the various integrations of this method, the wider application areas, and the international cooperation on this method are good topics to consider.

The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?

Tree Growth Algorithm (TGA)

A bi-objective sustainable supplier selection and order allocation considering quantity discounts under disruption risks: A case study in plastic industry

A bi-objective optimization for citrus closed-loop supply chain using Pareto-based algorithms

Designing and solving a bi-level model for rice supply chain using the evolutionary algorithms

In this paper, a hybrid multi-criteria decision-making (MCDM)-method and mixed integer linear programming (MILP) approach in order to evaluation of the returned products' collectors along with their ordered quantities, is utilized. Firstly, the most important criteria of collection center in the car industry are identified. Then, in order to evaluate these proposed criteria, a hybrid Fuzzy Decision-Making Trial And Evaluation Laboratory (FDEMATEL)- evaluation of mixed qualitative and quantitative data (EVAMIX) approach is applied. By this method, the most important criteria and their weights along with collection centers' score are determined. In addition, an MILP mathematical model is proposed for selection of the best collection center and computation of ordering quantities. An efficient approach for collection center selection and a novel application of combined FDEMATEL, EVAMIX, and MILP model can be considered as the main contributions of this paper. It should be noted that, to measure the performance of this method a recycling company as a case study in Iran has considered which of this firm collects effete tire and ball bearings of cars. Implementation of this case study can be considered as the other contributions of this paper. At last, with help of obtained results the proper collection center and their ordered quantities are computed. In addition, for measure efficiency of the proposed model, some numerical example, in various dimensions is considered. Moreover, the managers of this industry with the help of a simple methodology can choose the appropriate suppliers.

https://www.ije.ir/article_72974_9489f38f747cd4014e733f3ed1d49fdc.pdf

Armin Cheraghalipour

Papers

Tree Growth Algorithm (TGA)

A bi-objective sustainable supplier selection and order allocation considering quantity discounts under disruption risks: A case study in plastic industry

A bi-objective optimization for citrus closed-loop supply chain using Pareto-based algorithms

Designing and solving a bi-level model for rice supply chain using the evolutionary algorithms

An Integrated Approach for Collection Center Selection in Reverse Logistics