Multiple attribute decision making (MADM) methods are very useful in choosing the best alternative among the available finite but conflicting alternatives. TOPSIS is one of the MADM methods, which is simple in its methodology and logic. In TOPSIS, Euclidean distances of each alternative from the positive and negative ideal solutions are utilized to find the best alternative. In literature, apart from Euclidean distances, the city block distances have also been tried to find the separations measures. In general, the attribute data are distributed with unequal ranges and also possess moderate to high correlations. Hence, in the present paper, use of statistical distances is proposed in place of Euclidean distances. Procedures to find the best alternatives are developed using statistical and weighted statistical distances respectively. The proposed methods are illustrated with some industrial problems taken from literature. Results show that the proposed methods can be used as new alternatives in MADM for choosing the best solutions.

Vendor managed inventory (VMI) is one of the most effective methods for reducing bullwhip effect. This paper presents a mathematical VMI model where there are three levels of central storage, multi distribution centers and various retailors. The problem is formulated as a mixed integer programming by considering uncertainty on different input parameters. To cope with uncertainty, the study uses rectangular fuzzy numbers. We also propose two metaheuristics; namely, genetic algorithm and particle swarm optimization to solve the resulted problems for some large instances. The preliminary results have indicated that genetic algorithm could solve the proposed model faster than particle swarm optimization in terms of CPU time reaching to slightly better objective functions.

Nowadays enterprises should consider seeking to reduce the supply chain risks as a crucial part of their activities in order to improve their competitiveness in the international context. Choosing the suitable strategy in connection with assigning some parts of the production process to outside the organization is a complex multi-criteria decision making problem and it gets more complicated when supply chain risk factors as the factors to select the strategy as well as dependence and the close ties between these criteria also be considered. In this paper, after the identification of risks in the supply chain of a medical equipment manufacturer company, dependence and ties between criteria in line with choosing the best strategy among existing alternatives has been examined in the form of a combined ANP-ELECTRE method. This combined model is of high performance to give a solution to the problem considered in this paper. But given the complex and time consuming nature of the AHP and ELECTRE, in this study a meta-heuristic algorithm is developed called SIMANP that despite the simplicity of computing and high-speed, is good in the terms of precision and efficiency. The results of comparing SIMANP algorithm and the proposed ANP - ELECTRE method are presented at the end.

Weather forecasting is essential and demanding scientific task of meteorological services across the world. It is a complex procedure that includes many specific technological field of study. The prediction is intricate process in meteorology because all decisions are made within a facet of uncertainty associated with weather systems. This research finding introduces a novel rough fuzzy computing approach for a short term rainfall forecasts. The model consists of rough set based optimal weather parameter selection module and fuzzy rule based classification module. The proposed fuzzy decision support model is compared with benchmarked classification approaches. The fuzzy classification model used in fuzzy decision support system is trained and tested using the reduct sets generated using proposed maximum frequency weighted feature reduction technique. The optimal reduct set constituting the weather parameters; minimum temperature, relative humidity and solar radiation achieved better prediction accuracy than complete feature set and the reducts. Most of the classification models have shown better accuracy when trained using the selected subsets of the target input. Thorough evaluation of the proposed model has revealed that coupling fuzzy decision support system and rough based pre-processing techniques was a better approach than traditional techniques. The experimental results revealed the proposed rough fuzzy model as a better rainfall prediction approach for modeling short range rainfall forecast.

This paper presents the effect of Post Weld Heat Treatment (PWHT), pulsed current welding, hybrid welding and vibratory assisted welding in the weld quality, residual stresses and mechanical properties of welded joints. At last, vibratory assisted welding has been suggested to enhance the mechanical properties of welded joints by overcoming the drawbacks in the above stated techniques. Past results showed that the welded test specimens under vibratory conditions exhibited improvements in mechanical properties than the arc welding without vibrations. Finally, some literature gaps are clearly identified and these gaps could help the future generation researchers to do work in the new direction.

Underground gas pipelines are one of the vital parts of each country which surface blasts can break down such pipelines, making destructive explosions and threatening the safety of neighborhood structures and people. In this paper, to enhance the safety of these lines, response of a buried 56-inch diameter high pressure natural gas pipeline to a surface blast was numerically investigated. Besides, the effects of: i) explosive mass, ii) pipeline thickness, iii) burial depth and iv) concrete protective layer on pipeline deformation were parametrically studied. To simulate the problem according to actual explosion events, geometries were modeled in real scales, pipeline properties were predicted with Johnson-Cook strength and failure model and soil strength was determined by Drucker-Prager model. Also, explosive charge and natural gas were modeled with JWL (Jones-Wilkins-Lee) and ideal gas equation of states. For validation of the numerical method, three bench mark experiments were reproduced. Comparison of the numerical results and the experimental data confirmed the accuracy of the numerical method. Results of parametric studies indicated that by increasing the burial depth from 1.4 to 2.2 m, deformation of the pipeline was reduced about 71%. By analyzing the deformation plots, it was found that in a constant explosive mass, burial depth has a greater effect than pipeline thickness on pipeline deformation reduction. It was also shown that using a concrete protective layer may act reversely and increase pipeline destruction. In other words, to enhance the safety of pipelines, a certain thickness of concrete must be used.

A review of some recent data from multiaxial fatigue data from different notched materials is carried out in the paper. The approach based on the strain energy density (SED) averaged over a control volume is first used to summarise uniaxial and multiaxial fatigue strength data of welded joints made of structural steel and aluminium alloys. In all welded joints, the weld toe and weld root regions are modelled like sharp, zero radius, V-notches with different opening angles. The control volume radius is 0.28 mm for structural steels, 0.12 mm for aluminium alloys. Afterwards the SED approach is applied to multi-axial fatigue data from plain and V-notched specimens made of AISI 416 stainless steel (hardened and tempered state), subjected to tension, torsion and combined tension and torsion, both in-phase and out-of-phase. Notched specimens are characterised by a very small root radius, ρ=0.1 mm, which results in high nonlinear effects ahead of the notch tips. All results are summarised in terms of Δ W-N (SED range versus cycles to failure) scatterbands. Together with the new results, a number of multi-axial fatigue data recently obtained from sharply notched specimens made of C40 steel (normalised state) and 39NiCrMo3 steel (hardened and tempered state) are represented with the aim to provide a global synthesis in terms of local SED. Finally a synthesis from Ti6Al4V alloy is carried out showing the capability of the SED approach to be applied also to light alloys.

The problem of thermoelastic nanoscale beam based on a modified couple stress theory with diffusion subjected to ramp type heating is investigated. The Laplace transform technique and eigen value approach are applied to solve the equations which are written in the dimensionless form. The expressions for displacement, lateral deflection, temperature change, mass concentration, axial stress and chemical potential are derived in the transformed domain. A general algorithm of the inverse Laplace transform is developed to compute the results numerically. The mathematical model is prepared for Copper material. The resulting quantities are depicted graphically to show the effects of time. Some particular cases of interest are also deduced from the present problem.

The cost of road construction or its repair is among the most concerns for the pavements engineers. Cracking and degradation is common mode of failure in asphalt pavements that occurs due to increasing traffic loads or even environmental conditions. For facing with these damages, some solutions are proposed including correction, quality improvement and increasing the asphalt resistance. In this research, by adding different percent amounts of black nano-carbon and polyester fibers as modifier in the asphalt mixtures and conducting several Marshall tests, it was observed that adding these two additives can improve generally the Marshall results. Polyester fiber causes preventing crack and damages of asphalt because of armed effect specification. According to the results, Marshall stability is increased up to 61%. Furthermore, an economic analysis was performed to investigate the cost of using such modified asphalt mixtures for constructing 1 km of a six line road and suitable percentages of additives were found from mechanical-economic analyses.

Portland cement concrete (PCC) / asphalt concrete (AC) bonded components are seen in both conventional pavement structures as well as overlays. Due to the environmental and traffic loads, cracks occur at the interface of the PCC and AC layers and finally, may propagate through the interface or one of the layers. Therefore, the evaluation of bond strength between these layers is important. This paper investigates bond strength between asphalt concrete and Portland cement concrete using a new sandwich test specimen. The developed specimen, called Bi-material semi-circular bend (BSCB) is made of asphalt concrete and the Portland cement concrete, cracked at the interface of the materials. First, the suggested specimen is introduced and characterized using finite element simulation. Then, the specimen is employed to obtain bond strength between asphalt concrete and Portland cement concrete under mixed mode loading, and at two temperatures: -20C and 20C. The fracture toughness at different mixed mode conditions is obtained, and finally, fracture criterion for the tested bonded joints is presented.