The capacitated arc routing problem is one of the most important routing problems with many applications in real world situations such as snow removing, winter gritting, refuse collection, etc. Since this problem is NP-hard, many of researchers have been developed numerous heuristics and metaheuristics to solve it. In this paper, we propose a new constructive and improvement heuristic in which forming a vehicle’s tour is based on choosing an unserved edge randomly as current partial tour and then extending this partial tour from its both of end nodes base on four effective proposed criteria. When the vehicle load is near its capacity, it should come back to the depot immediately. Finally, the constructed tours are merged into more efficient and cheaper tours. The quality of this new approach was tested on three standard benchmark instances and the results were compared with some known existing heuristics and metaheuristics in the literature. The computational results show an excellent performance of our new method.

Cross docking play an important role in management of supply chains where items delivered to a warehouse by inbound trucks are directly sorted out, reorganized based on customer demands, routed and loaded into outbound trucks for delivery to customers without virtually keeping them at the warehouse. If any item is held in storage, it is usually for a short time, which is normally less than 24 hours. The proposed model of this paper considers a special case of cross docking where there is temporary storage and uses GRASP technique to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using GRASP method. The preliminary test results indicate that the GRASP method performs better than alternative solution strategies.

In this paper, an integrated layout model has been considered to incorporate intra and inter-department layout. In the proposed model, the arrangement of facilities within the departments is obtained through the QAP and from the other side the continuous layout problem is implemented to find the position and orientation of rectangular shape departments on the planar area. First, a modified version of QAP with fewer binary variables is presented. Afterward the integrated model is formulated based on the developed QAP. In order to evaluate material handling cost precisely, the actual position of machines within the departments (instead of center of departments) is considered. Moreover, other design factors such as aisle distance, single or multi row intra-department layout and orientation of departments have been considered. The mathematical model is formulated as mixed-integer programming (MIP) to minimize total material handling cost. Also due to the complexity of integrated model a heuristic method has been developed to solve large scale problems in a reasonable computational time. Finally, several illustrative numerical examples are selected from the literature to test the model and evaluate the heuristic.

In this paper, a new optimization technique known as Teaching–Learning-Based Optimization (TLBO) is implemented for solving high dimensional function optimization problems. Even though there are several other approaches to address this issue but the cost of computations are more in handling high dimensional problems. In this work we simulate TLBO for high dimensional benchmark function optimizations and compare its results with very widely used alternate techniques like Differential Evolution (DE) and Particle Swarm Optimization (PSO). Results clearly reveal that TLBO is able to address the computational cost issue for all simulated functions to a large dimensions compared to other two techniques.

Cost estimation of new products has always been difficult as only few design, manufacturing and operational features will be known. In these situations, parametric or non-parametric methods are commonly used to estimate the cost of a product given the corresponding cost drivers. The parametric models use priori determined cost function where the parameters of the function are evaluated from historical data. Non-parametric methods, on the other hand, attempt to fit curves to the historic data without predetermined function. In both methods, it is assumed that the historic data used in the analysis is a true representation of the relation between the cost drivers and the corresponding costs. However, because of efficiency variations of the manufacturers and suppliers, changes in supplier selections, market fluctuations, and several other reasons, certain costs in the historic data may be too high whereas other costs may represent better deals for their corresponding cost drivers. Thus, it may be important to rank the historic data and identify benchmarks and estimate the target costs of the product based on these benchmarks. In this paper, a novel adaptation of cost drivers and cost data is introduced in order to use data envelopment analysis for the purpose of ranking cost data and identify benchmarks, and then estimate the target costs of a new product based on these benchmarks. An illustrative case study has been presented for the cost estimation of landing gears of an aircraft manufactured by an aerospace company located in Montreal, CANADA.

In many real-world applications, the quality of a process or a particular product can be characterized by a functional relationship called profile. A profile builds the relationships between a response quality characteristic and one or more explanatory variables. Monitoring the quality of a profile is implemented to understand and to verify the stability of this functional relationship over time. In some real applications, a fuzzy linear regression model can represent the profile adequately where the response quality characteristic is fuzzy. The purpose of this paper is to develop an approach for monitoring process/product profiles in fuzzy environment. A model in fuzzy linear regression is developed to construct the quality profiles by using linear programming and then fuzzy individuals and moving-range (I-MR) control charts are developed to monitor both intercept and slope of fuzzy profiles to achieve an in-control process. A case study in customer satisfaction is presented to show the application of our approach and to express the sensitivity analysis of parameters for building a fuzzy profile.

Maximization of flow through the network is required in many practical applications such as water supply flow networks, Oil and Gas flow networks, and transportation networks etc. In this paper a new theorem is presented that has direct application on maximization of flow through the network. This theorem suggests that the maximization of network flow can be achieved by visiting only unbalanced nodes rather than the whole network. Therefore based on this theorem a method is developed that maximizes flow thorough the network by visiting only unbalanced nodes. Hence this method can achieve solution in a sub-linear time where network has fewer unbalanced nodes. However this method has worst case complexity of order O(m2-m), where m is the number of edges. Furthermore it is shown that this theorem has also potential to make optimization an easier task in a multi-commodity flow environment.

Mutual fund is one of the most popular techniques for many people to invest their funds where a professional fund manager invests people & apos; s funds based on some special predefined objectives; therefore, performance evaluation of mutual funds is an important problem. This paper proposes a multi-objective portfolio optimization to offer asset allocation. The proposed model clusters mutual funds with two methods based on six characteristics including rate of return, variance, semivariance, turnover rate, Treynor index and Sharpe index. Semivariance is used as a downside risk measure. The proposed model of this paper uses fuzzy variables for return rate and semivariance. A multi-objective fuzzy mean-semivariance portfolio optimization model is implemented and fuzzy programming technique is adopted to solve the resulted problem. The proposed model of this paper has gathered the information of mutual fund traded on Nasdaq from 2007 to 2009 and Pareto optimal solutions are obtained considering different weights for objective functions. The results of asset allocation, rate of return and risk of each cluster are also determined and they are compared with the results of two clustering methods.

The dynamics of human resource recruitment and training in an uncertain environment creates a challenge for many policy makers in various organisations. In the presence of fuzzy manpower demand and training capacity, many companies fear losing critical human resources when their employees leave. As such, the development of effective dynamic policies for recruitment and training in a fuzzy dynamic environment is imperative. In this frame of mind, a fuzzy systems dynamics modelling approach is proposed to enable the policy maker to develop reliable dynamic policies relating recruitment, training, and available skills, from a systems perspective. It is anticipated in this study that fuzzy system dynamics and optimization approach would help organizations to design effective manpower policies and strategies.

Wire electrical discharge machining (WEDM) is well known process for generating intricate and complex profiles in hard metal matrix composites. But damaged surface layer with poor surface integrity is a major disadvantage of WEDM. Beside poor damaged surface layer, after rough/first cut in WEDM, some surface area remains unmachined on work surface during intricate machining such as in die cutting. This paper presents a study on unmachined surface area named as surface projection, in die cutting after rough cut in WEDM. Using scanning electron microscope images, length of unmachined surface projections have been determined. In order to minimize these surface projections from small cavities having complex geometries, trim cutting operation is the best alternative. Results show that using more than one trim cut with appropriate wire offset value, surface projections can be minimized, successfully.