Wind farms are designed to supply power to the consumers at a minimal price. The cost of wind power production directly or indirectly depends on proper selection of vendors. The present paper highlights a model for selection and ranking of vendors for a wind farm based on fuzzy set theory to determine criteria weights and an additive ratio assessment (ARAS) method to analysis criteria values. The objective of the paper is to establish the ARAS method as an effective method for Vendor selection. A case study is shown to ascertain the proposed method especially when the criteria are interdependent and conflicting in nature. The result is validated with another popular MCDM technique, COPRAS, which shows that the models are effective and applicable, and provide decision makers with better solutions for decision making.

Differential Search (DS) algorithm is a new meta-heuristic for solving real-valued numerical optimization. This paper introduces a new method based on DS for solving Resource Constrained Project Scheduling Problem (RCPSP). The RCPSP is aimed to schedule a set of activities at minimal duration subject to precedence constraints and the limited availability of resources. The proposed method is applied to PSPLIB case studies and its performance is evaluated in comparison with some of state of art methods. Experimental results show that the proposed method is effective. Also, it is among the best algorithms for solving RCPSP.

This study presents optimization of performance characteristics in unidirectional glass fiber reinforced plastic composites using Taguchi method and Grey relational analysis. Performance characteristics such as surface roughness and material removal rate are optimized during rough cutting operation. Process parameters including tool nose radius, tool rake angle, feed rate, cutting speed, cutting environment and depth of cut are investigated using mixed L18 orthogonal array. Grey relation analysis is used to optimize the parameters and Principal Component Analysis is used to find the relative significance of performance characteristics. Depth of cut is the factor, which has great influence on surface roughness and material removal rate, followed by feed rate. The percentage contribution of depth of cut is 54.399% and feed rate is 5.355%.

In the context of supply chain management, supplier selection plays a key role in reaching desirable production planning. In today & apos; s competitive world, many enterprises have focused on selecting the appropriate suppliers in an attempt to reduce purchasing costs and improve quality products and services. Supplier selection is a multi-criteria decision problem, which includes different qualitative and quantitative criteria such as purchase cost, on time delivery, quality of service, etc. In this study, a fuzzy multi-objective mathematical programming model is presented to select appropriate supplier and assign desirable order to different supplies. The proposed model was implemented for an organization by considering 16 different scenarios and the results are compared with two other existing methods.

This paper considers a multi-objective version of the Multiple Traveling Salesman Problem (MOmTSP). In particular, two objectives are considered: the minimization of the total traveled distance and the balance of the working times of the traveling salesmen. The problem is formulated as an integer multi-objective optimization model. A non-dominated sorting genetic algorithm (NSGA-II) is proposed to solve the MOmTSP. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. Tests on real world instances and instances adapted from the literature show the effectiveness of the proposed algorithm.

Keeping in view the concern about environmental protection, the study investigates effects of remanufacturing in an integrated production inventory model consisting of forward and reverse supply chain over infinite planning horizon. This article is developed for the deteriorating products with stock dependent demand under shortages. To make the model more realistic, flexibility of production system has been incorporated during forward manufacturing. We derive total cost function and using the results of calculus, optimum production policy is derived, which minimizes the total cost incurred. The results are discussed with a numerical example to illustrate the theory.

The main aim of the present paper is to analyze the stochastic behavior of a cold standby system with concept of preventive maintenance, priority and maximum repair time. For this purpose, a stochastic model is developed in which initially one unit is operative and other is kept as cold standby. There is a single server who visits the system immediately as and when required. The server takes the unit under preventive maintenance after a maximum operation time at normal mode if one standby unit is available for operation. If the repair of the failed unit is not possible up to a maximum repair time, failed unit is replaced by new one. The failure time, maximum operation time and maximum repair time distributions of the unit are considered as exponentially distributed while repair and maintenance time distributions are considered as arbitrary. All random variables are statistically independent and repairs are perfect. Various measures of system effectiveness are obtained by using the technique of semi-Markov process and RPT. To highlight the importance of the study numerical results are also obtained for MTSF, availability and profit function.

Turning hardened component with PCBN and ceramic inserts have been extensively used recently and replaces traditional grinding operation. The use of inexpensive multilayer coated carbide insert in hard turning is lacking and hence there is a need to investigate the potential and applicability of such tools in turning hardened steels. An attempt has been made in this paper to have a study on turning hardened AISI 4340 steel (47 ± 1 HRC) using coated carbide inserts (TiN/TiCN/Al2O3/ZrCN) under dry environment. The aim is to assess the tool life of inserts and evolution of flank wear with successive machining time. From experimental investigations, the gradual growth of flank wear for multilayer coated insert indicates steady machining without any premature tool failure by chipping or fracturing. Abrasion is found to be the dominant wear mechanisms in hard turning. Tool life of multilayer coated carbide inserts has been found to be 31 minute and machining cost per part is Rs.3.64 only under parametric conditions chosen i.e. v = 90 m/min, f = 0.05 mm/rev and d = 0.5 mm. The mathematical model shows high determination coefficient, R2 (99%) and fits the actual data well. The predicted flank wear has been found to lie very close to the experimental value at 95% confidence level. This shows the potential and effectiveness of multilayer coated carbide insert used in hard turning applications.

Distribution and optimum allocation of emergency resources are the most important tasks, which need to be accomplished during crisis. When a natural disaster such as earthquake, flood, etc. takes place, it is necessary to deliver rescue efforts as quickly as possible. Therefore, it is important to find optimum location and distribution of emergency relief resources. When a natural disaster occurs, it is not possible to reach some damaged areas. In this paper, location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling is investigated. In this study, there is no need to visit all the places and some demand points receive their needs from the nearest possible location. The proposed study is implemented for some randomly generated numbers in different sizes. The preliminary results indicate that the proposed method was capable of reaching desirable solutions in reasonable amount of time.

The bullwhip effect is a phenomenon in forecast-driven distribution channels, which is associated with a trend of larger and larger swings in inventory in response to changes in demand, as we look at firm further back in the supply chain for a particular product. This paper deals with the bullwhip effect in a multi-echelon multiple products supply chain with correlated market demands. The downstream retailer procures products from an un-capacitated upstream supplier to meet the correlated market demands of multiple products. This paper proposes a new method based on demand forecasting technique and uses a simple moving average to eliminate the bullwhip effect, which is proved to be effective under some circumstances.