In this paper, a robust bi-level model is proposed to optimize decisions related to distribution and evacuation aid after earthquake. Usually in disastrous situation foreign countries help the affected country by sending relief commodities. In this problem, the foreign countries try to minimize their shipping costs and the affected country seeks to minimize its total costs which include inventory, operation, and transportation expenses. This situation is a game between different decision makers after a catastrophic disaster. To deal with this situation, a bi-level model is proposed in which the affected country is the leader and suppliers are the followers. To validate the proposed robust model, we consider Tehran probable earthquake in region 1 as a case study. Then the advantages of using bi-level modeling against considering just one player's point of view is provided. The sensitivity analysis of the experiments are presented to explore the effects of various parameters to show managerial insights that can guide DMs under a variety of conditions.

In this study, an ensemble algorithm has been proposed, called Quasi-Oppositional Symbiosis Organisms Search (QOSOS) algorithms, by incorporating the quasi-oppositional based learning (QOBL) strategy into the newly proposed Symbiosis Organisms Search (SOS) algorithm for solving unconstrained global optimization problems. The QOBL is incorporated into the basic SOS algorithm due to the balance of the exploration capability of QOBL and the exploitation potential of SOS algorithm. To validate the efficiency and robustness of the proposed Quasi-Oppositional Symbiosis Organisms Search (QOSOS) algorithms, it is applied to solve unconstrained global optimization problems. Also, the proposed QOSOS algorithm is applied to solve two real world global optimization problems. One is gas transmission compressor design optimization problem and another is optimal capacity of the gas production facilities optimization problem. The performance of the QOSOS algorithm is extensively evaluated and compares favorably with many progressive algorithms.

The revolutionary alterations and conversions occurring in information and communication technologies, have triggered an increase in the electronic commerce applications. Airline tickets are one of the most popular items purchased on the internet. The airline websites have become a big distribution channel for the companies to sustain their competitiveness. At this moment, the competition is increasing as airlines try to acquire and retain customers in the airline industry. To acquire and retain customers in such a highly competitive market, it is important for airlines to understand their relative levels of quality in terms of critical elements affecting their competitive advantages. In this study, an integrated two-stage multi-criteria decision-making techniques were used for the measurement of the performance of the airline websites using the Entropy Weight Method and the Grey Relational Analysis approach. The performance of 11 airline companies’ websites operating in Turkey was evaluated in terms of seven criteria. The data of quality website from airlines websites were taken more than 30 trails on various occasions on different periods of times. The data has been taken from 1 December 2016 to 31 December 2016. The weights of the attributes were calculated by Entropy Weight Method, the evaluation of the alternatives using the Grey Relational Analysis method were given ranking of websites.

Application of Artificial Neural Network (ANN) in modeling of combined cycle power plant (CCPP) with dry cooling tower (Heller tower) has been investigated in this paper. Prediction of power plant output (megawatt) under different working conditions was made using multi-layer feed-forward ANN and training was performed with operational data using back-propagation. Two ANN network was constructed for the steam turbine (ST) and the main cooling system(MCS). Results indicate that the ANN model is effective in predicting the power plant output with good accuracy.

Multi-criteria decision making approach is one of the most troublesome tools for solving the tangled optimization problems in the machining area due to its capability of solving the complex optimization problems in the production process. Turning is widely used in the manufacturing processes as it offers enormous advantages like good quality product, customer satisfaction, economical and relatively easy to apply. A contemporary approach, MOORA coupled with PCA, was used to ascertain an optimal combination of input parameters (spindle speed, depth of cut and feed rate) for the given output parameters (power consumption, average surface roughness and frequency of tool vibration) using L27 orthogonal array for turning on ASTM A588 mild steel. Comparison between MOORA-PCA and TOPSIS-PCA shows the effectiveness of MOORA over TOPSIS method. The optimum parameter combination for multi-performance characteristics has been established for ASTM A588 mild steel are spindle speed 160 rpm, depth of cut 0.1 mm and feed rate 0.08 mm/rev. Therefore, this study focuses on the application of the hybrid MCDM approach as a vital selection making tool to deal with multi objective optimization problems.

The present paper deals with the experimental analysis and multi objective optimization of gear cutting process of Inconel 718 using WEDM. The objective of the present work is to optimize the parameters in order to maximize the material removal rate and minimize the kerf in a gear cutting process to get the optimum value. The MRR and kerf play a major role in optimizing the parameters in WEDM process. The experiment is carried out in the wire EDM machine using brass wire as the electrode, Inconel 718 as the work-piece material and distilled water as the dielectric. The design array is created by using Design of Experiment in a Taguchi L16 orthogonal array repeated once. The gear has a base diameter of 20 mm, addendum diameter of 22.5 mm and a pressure angle of 20º with 16 numbers of teeth. The machining operation is carried out by taking 3 input parameters at 4 different levels each. The output parameters such as Material Removal rate and Kerf width were obtained and optimized using TOPSIS method to know the optimum setting. Microstructural analysis of both material and wire were studied to know the various defects during the machining operation. Various plots were obtained to know the effects of the process parameters in WEDM. A regression model was also obtained to validate the statistical model values with the experimental. ANOVA table and Response table were carried out to know the significant parameters and rank respectively in the Wire EDM process. Surface roughness, Addendum and Tooth width of gears were also found out at the optimum settings. The optimum setting of the gear obtained can be used to produce high quality gears and can also be applied for future findings.

In this paper, a heuristic algorithm based on Tabu Search Approach for solving the Vehicle Routing Problem with Backhauls (VRPB) is proposed. The problem considers a set of customers divided in two subsets: Linehaul and Backhaul customers. Each Linehaul customer requires the delivery of a given quantity of product from the depot, whereas a given quantity of product must be picked up from each Backhaul customer and transported to the depot. In the proposed algorithm, each route consists of one sub-route in which only the delivery task is done, and one sub-route in which only the collection process is performed. The search process allows obtaining a correct order to visit all the customers on each sub-route. In addition, the proposed algorithm determines the best connections among the sub-routes in order to obtain a global solution with the minimum traveling cost. The efficiency of the algorithm is evaluated on a set of benchmark instances taken from the literature. The results show that the computing times are greatly reduced with a high quality of solutions. Finally, conclusions and suggestions for future works are presented.

New product development is a modern approach to deal with the environmental changes and an introduction to enter the competitive atmosphere is a challenging condition. By realizing the critical aspects of success of the new product and selecting a compatible model of variables in these aspects, companies may create a unique context for developing the product; but whether in terms of the multiplicity of the decision-making choices or the inherent conflicts of the response atmosphere’s variables, the complexities of the current world have caused disruption and inefficiency in the field of optimal selection and decision making. The aim of this study is to identify the critical aspects of development of the new product in the Sedan automobile class and to offer a morphological model of that by investigating the ideas and comments of the experts and scholars. In this regard, by using the Importance-Performance Analysis (IPA) method, the proposed method assesses the mode of the organization; and with the General Morphological Analysis, it assesses and searches for the most compatible decision-making variables to find the fully optimal and compatible solutions. After studying the subject literature, seven critical aspects are selected for the product development and three purposes are chosen for limiting the morphological model. Finally, four fully compatible configurations and one configuration are proposed with the entrance of the aspects determined from the output of IPA method. The innovative solution in solving the morphological model and its integration with IPA method are considered as the innovations of this study.

In an environment where markets go through a volatile process, and rapid fundamental changes occur due to technological advances, it is important to ensure and maintain a good performance measurement. Organizations, in their performance evaluation, should consider different types of financial and non-financial indicators. In systems like direct sales stores in which decision units have multiple inputs and outputs, all criteria influencing on performance must be combined and examined in a system, simultaneously. The purpose of this study is to evaluate the performance of different products through direct sales of a firm named Shirin Asal with a combination of Balanced Scorecard, fuzzy AHP and TOPSIS so that the weaknesses of subjectivity and selective consideration of evaluators in evaluating the performance indicators are reduced and evaluation integration is provided by considering the contribution of each indicator and each indicator group of balanced scorecard. The research method of this case study is applied. The data collection method is a questionnaire from the previous studies, the use of experts' opinions and the study of documents in the organization. MATLAB and SPSS were used to analyze the data. During this study, the customer and financial perspectives are of the utmost importance to assess the company branches. Among the sub-criteria, the rate of new customer acquisition in the customer dimension and the net income to sales ratio in financial dimension are of the utmost importance.

There is a little research about the relationship between risk and technology by using the DEMATEL model in a complex systems such as maritime port. Those studies neither include nor identify the relationships of technological risk generated between a Port Community and all the other actors who interact with it. This study presents the potential advantage of applying the DEMATEL to identify the synergic relationships at strategic and business levels produced by technological risk. The results determine the causes and the effects of decisions made by managers of port engineering community. They also affect the processes of information and communication logistics chains’ export and import.