E-commerce is one of the industries most affected by big data, from collection to analytics in the highly competitive market. Previous research on big data analytics in E-commerce focused only on particular applications, and there is still a gap in presenting a framework to evaluate big data applications from a challenges-values point of view. This study employs a three-phase methodology to evaluate big data applications in E-commerce with respect to big data challenges and values using a hybrid multi-criteria decision-making technique that combines BWM and fuzzy TOPSIS. The results showed process challenge and the strategic value obtained the highest weight for challenges and values criteria. Financial fraud detection is relatively the most challenging, and online review analytics is the most valuable application of big data in E-commerce among identified applications. Evaluating big data applications based on cost and benefit criteria is practical for E-commerce managers and experts to make decisions on implementation priorities to overcome the challenges and make the most of values. Moreover, the proposed approach is not only limited to big data analytics in E-commerce and can also be applied in other industries to evaluate emerging technology applications.

The dynamic behavior of the cylindrical shell can be predicted by more simplified beam models for a wide range of applications. The present paper deals with finding design conditions in which the cylindrical shell performs like a beam. Employing the Hamilton’s principle, the governing equations are obtained using both Donnell-Mushtari and Flugge shell theories and the analytical solution is obtained for long cylinders with simply-supported boundary conditions at both ends. Then, by equalizing the shell and beam vibration frequencies, the shell-to-beam transition conditions are obtained for both theories. To account for the effects of shear distortion and rotatory inertia of the shell, the finite element method is applied to find the best transition conditions with less approximating assumptions. Finally, the effects of boundary conditions on the transition parameters as well as the frequency response are studied. The obtained conditions simply define that if the shell can be assumed as a beam in any specific geometrical and material conditions.

This paper presents a mathematical model for a single depot, time-dependent vehicle routing problem with backhaul considering the first in first out (FIFO) assumption. As the nature of the problem is NP-hard, variable neighborhood search (VNS) meta-heuristic and mat-heuristic algorithms have been designed. For test problems with large scales, obtained results highlight the superior performance of the mat-heuristic algorithm compared with that of the other algorithm. Finally a case study at the post office of Khomeini-Shahr town, Iran, was considered. Study results show a reduction of roughly 19% (almost 45 min) in the travel time of the vehicle.

In reality, concrete structures are normally under various loadings, and results of different studies have shown that cracks in these structures and their materials, due to their nature as well as the loading type, do not develop along the crack plane (pure mode I); rather, they expand under mixed modes, making the crack growth studies under these modes a very important issue. In the crack growth phenomenon, the fracture toughness is a very effective parameter usually calculated by ENDB samples because they are easy to handle. In this study, several samples were made by changing the maximum aggregates size (dmax = 9.5, 12.5 & 19 mm) and the amount of hooked-end steel fibers (SF = 0.1, 0.3 & 0.5%), and tested under different loading modes (pure/mixed modes I and III) using the strain control jack device. According to the results, the lowest fracture toughness belonged to pure mode III, aggregates with dmax = 12.5 mm performed better in the self-compacting concrete reinforced with steel fiber, Also, the results show that the increasing trend of steel fibers does not have a positive effect on the fracture toughness performance.

Quality profiles representing the quality of a process or product as the functional relationship between one or more dependent variables and one or more explanatory variables are nowadays widely recognized in statistical process control (SPC) applications by both researchers and practitioners. On the other hand, in many real-world cases, evaluation of process or product characteristics is carried out with ambiguity or conducted using linguistic values. The theory of fuzzy sets provides an appropriate approach to deal with uncertainty due to ambiguity in human subjective evaluations or vagueness in linguistic variables. The purpose of this study is to introduce two novel methods based on fuzzy regression modeling for monitoring fuzzy linear profiles in phase II of SPC. To accomplish this, fuzzified Hoteling’s T2 statistic and fuzzy hypothesis testing are used. Moreover, a simulation study is used to compare the performance of the proposed methods compared with previous methods, based on the average run length (ARL) criterion in order to assess the detectability of charts with regard to the step shifts in profile parameters. Finally, the results of a real-world example in the tile and ceramic industry are presented.

In this article, the application of the Multi-Skilled Resource-Constrained Flow Shop Scheduling Problem (MSRC-FSSP) in preventive maintenance as a case study has been investigated. In other words, to complete each maintenance order at each stage, in addition to the machine, a set of required human resources with different skills must be available. According to human resources skills, each of them can perform at least one order or at most N orders, and each maintenance order must be done by a set of human resources with different skills. To carry out a maintenance order, different human resources must be in communication and cooperation so that a preventive maintenance order can be completed. In this article, these resources are considered as technical supervisors, repairmen and maintenance managers who complete all maintenance orders in a flow shop environment as a job. For this problem, a new Mixed Integer Linear Programming (MILP) model has been formulated with the two-objective functions, minimizing total orders completion time and the human resources idle time. To solve the model on a small scale, CPLEX is used, and to solve it on a large scale, due to the fact that this problem is NP-Hard, a meta-heuristic algorithm named Genetic Algorithm (GA) is presented. Finally, the computational results have been done to validate the model, along with the analysis of the human resources idle time.

In this paper, a memory-based simulated annealing algorithm called the Dual Memory Simulated Annealing Algorithm (DMSA) is presented to solve multi-line facility layout problems. The objective is to minimize the total material handling cost. Two memory buffers and a restart mechanism are considered. Two benchmark problems were selected from the literature review papers and solved using the standard simulated annealing (SA) algorithm and the DMSA. The obtained results show that solutions provided by the DMSA algorithm are cost-effective compared to the standard SA algorithm and the other algorithms used for solving these test cases. Moreover, to further evaluate the performance of the DMSA algorithm in large scale problems, eleven test cases were selected from the benchmark library of the quadratic assignment problem (QAP). According to the results, the performance of the algorithm in finding solutions to complex problems is exemplary.

In this research, a maximal covering location problem (MCLP) with real-world constraints such as multiple types of facilities and vehicles with different setup costs is taken into account. An original mixed integer linear programming (MILP) model is constructed in order to find the optimal solution. Since the problem at hand is shown to be NP-hard, a constructive heuristic method and a meta-heuristic approach based on genetic algorithm (GA) are developed to solve the problem. To find the most effective solution technique, a set of problems of different sizes is randomly generated and solved by the proposed solution methods. Computational results demonstrate that the heuristic method is capable of producing optimal or near-optimal solutions in a rational execution time.

Micro/mesopore composite catalysts containing platinum with HZSM-5 zeolite and three different silicate mesopores (SBA-3, KIT-6, and KCC-1) were prepared to investigate the influence of different silicate mesopores in the isomerization reaction of n-heptane at the temperature of 200-350 °C The structural characteristics and morphology of the prepared catalysts were studied by various methods such as XRD, FT-IR, N2 adsorption-desorption, XRF, and SEM. The obtained results indicate that the prepared catalysts have high conversion and high selectivity of multi-branched isomers compared to mono-branched isomers and low development of aromatic compounds. The most suitable results and selectivity were obtained in the n-heptane isomerization reaction related to the Pt/HZSM-5-SBA-3 catalyst.

The push-off phase is a critical part of initiating movement during walking, and it requires a significant amount of energy. Recent research has shown that the passive use of springs in parallel with the leg can harvest the push-off energy and reduce the total metabolic energy of walking for healthy subjects. In this study, we present the design of a prosthetic leg with a passive-based mechanism to reduce walking energy consumption for above-knee amputees. The mechanism stores energy during the stance phase of the gait cycle and releases it to support the prosthetic leg during locomotion. The known polycentric knee joint 3R36 and the ankle-foot joint ESAR were chosen and adopted for this study. We also utilized a ratchet clutch that connects with a spring and rope from the pylon to the foot which regulates movement and saves energy. Our simulations demonstrate that the spring stores elastic energy from approximately 22% of the gait cycle and reaches its maximum energy storage at approximately 50% of the walking cycle. The energy is then released at approximately 58% of the stride cycle during the push-off phase. The motion of the proposed prosthetic leg for individuals with transfemoral amputations mimics the normal walking pattern of healthy individuals well.