JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL
Year:2005 | Volume:1 | Issue:1|Papers Count:8

This paper proposes a hybrid method to find cumulative distribution function (CDF) of completion time of GERT-type networks (GTN) which have no loop and have only exclusive-or nodes. Proposed method is created by combining an analytical transformation with Gaussian quadrature formula. Also the combined crude Monte Carlo simulation and combined conditional Monte Carlo simulation are developed as alternative methods of solution procedure. Then, through a comparative study made for different solution procedures, the superiority of hybrid method is indicated. Computing time and accuracy are considered as fundamental factors for comparison purposes.

The one-dimensional cutting stock problem has so many applications in lots of industrial processes and during the past few years has attracted so many researchers’ attention all over the world. In this paper a metaheuristic method based on ACO is presented to solve this problem.In this algorithm, based on designed probabilistic laws, artificial ants do select various cuts and then select the best patterns. Also because of the problem framework, effective improvements have been made to problem solving process. The results of that algorithm in sample problems, show high efficiency of the algorithm in different levels of problems.

Process capability indices show the ability of a process to produce products according to the pre-specified requirements. Since final quality characteristics of a product are usually interrelated to its previous amounts in earlier workstations, one need to model and consider the relationship among them to assess the process capability properly. Hence, conducting process capability analysis in multivariate environment is inevitable; unfortunately, the analysis in multivariate environment is usually complex and requires extensive calculations. Sometimes it is preferable to simplify the analysis by assuming independency among quality characteristics and evaluating process performance with respect to each individual quality characteristic using univariate process capability indices such as CP, CPK, CPM, and CPMK. However, this simplification introduces some error in the analysis leading to under or overestimation of the process capability index. This paper models the interrelationship among quality characteristics that are produced in different workstations to provide an overall process capability index. Ridge residual regression is used as a vehicle to evaluate process capability and helps quality engineers to provide a reasonable quality policy for controlling and reducing variation in quality characteristics.

This paper presents a multi-criteria vehicle routing problem with soft time windows (VRPSTW) to minimize fleet cost, routes cost, and violation of soft time windows penalty. In this case, the fleet is heterogeneous. The VRPSTW consists of a number of constraints in which vehicles are allowed to serve customers out of the desirable time window by a penalty. It is assumed that this relaxation affects customer satisfaction and penalty is equal to a degree of customer dissatisfaction. The VRP, which is an extension of traveling salesman problem (TSP), belongs to a class of NP-hard problems. Thus, it is necessary to use meta-heuristics for solving VRP in large-scale problems. This paper uses a simulated annealing (SA) approach with 1-Opt and 2- Opt operators for solving the proposed mathematical model. The proposed model is then solved by the Lingo software and the associated solutions are compared with the computational results obtained by the SA approach for a number of instance problems. The obtained results are promising and indicating the efficiency of the proposed SA approach.

Teams are defined as high performing task groups whose members are actively interdependent and share common performance objectives. This definition suggests that only those groups who perform at high levels due to their collective efforts must be considered as teams. In this paper, a model has been presented for determining the effects of information technology in the output of teamwork with Y structure for particular productive organizations.

In this paper, the researchers present a multi-objective linear fractional inventory model using fuzzy programming. The proposed method in this paper is applied to a problem with two objective functions. The resulted fuzzy model is transformed into an ordinary linear programming. The implementation of the developing model presented in this paper is demonstrated through the use of some numerical examples.

In many infeasible linear programs it is important to construct it to a feasible problem with a minimum parameters changing corresponding to a given nonnegative vector. This paper defines a new inverse problem, called “inverse feasible problem”. For a given infeasible polyhedron and an n-vector x0 a minimum perturbation on the parameters can be applied and then a feasible polyhedron is concluded.

Data Envelopment Analysis (DEA) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. It represents a set of linear programming techniques and uses deterministic data (inputs and outputs), in stable conditions. The DEA technique cannot be used when there is data with in deterministic nature, or when there is an environment with dynamic conditions. To address this problem, DEA models can be developed based on linear programming in fuzzy environments (Fuzzy DEA). Most Fuzzy DEA models introduced in the literature are parametric models based on alpha cuts. However, the model introduced in this study is non-parametric and uses fuzzy L-R numbers. From the theory point of view, the objective of this study is to develop a simple and effective Fuzzy DEA model. From the practicality point of view, this model can be applied to assess many issues associated with qualitative factors.