A Mixed 0-1 Linear program for the Inspection Location Problem

An economic model is developed for determining optimal locations of screening inspection stations in a multistage production system. The effect of screening inspection on the production rate is explicitly considered, and a fixed cost for maintaining an inspection station is assumed. The product is allowed to have multiple defects, each of which may be inspected at any inspection station after the defect-generating operation. The problem is formulated as a mixed 0-1 linear program which offers the advantage of versatility in handling various system constraints

A Study on Warfighting Experimentation for Organizing Operational Troops

Warfighting experimentation is an important process for identifying requirements against changing military environment and for verifying proposed measures for reforming military service. The wargame simulation experiment is regarded as one of the most effective means to warfighting experimentation, and its importance is increasing than ever. On the other hand, the results of wargame experiments could be unreliable due to the uncertainty involved in the experimental procedure. To improve the reliability of the experimental results, systematic experimental procedures and analysis methods must be employed, and the design and analysis of experiments technique can be used effectively for this purpose. In this paper, AWAM, a wargame simulator, is used to optimize the organization of operational troops. The simulation model describes a warfighting situation in which the survival rate of our force and the survival rate of the enemy force are considered as responses, the numbers of weapons in the squad as control factors, and the uncontrollable variables of the battlefield as noise factors. In addition, for the purpose of effective experimentation, the product array approach in which the inner and outer orthogonal arrays are crossed is adopted. Then, the signal-to-noise-ratio for each response and the desirabilities for the means and standard deviations of responses are calculated and used to determine a compromise optimal solution. The experimental procedures and analysis methods developed in this paper can provide guidelines for designing and analyzing wargame simulation experiments for similar warfighting situations

Development of Reliability Analysis Procedures for Repairable Systems with Interval Failure Time Data and a Related Case Study

The purpose of this paper is to develop reliability analysis procedures for repairable systems with interval failure time data and apply the procedures for assessing the storage reliability of a subsystem of a certain type of guided missile. In the procedures, the interval failure time data are converted to pseudo failure times using the uniform random generation method, mid-point method or equispaced intervals method. Then, such analytic trend tests as Laplace, Lewis-Robinson, Pair-wise Comparison Nonparametric tests are used to determine whether the failure process follows a renewal or non-renewal process. Monte Carlo simulation experiments are conducted to compare the three conversion methods in terms of the statistical performance for each trend test when the underlying process is homogeneous Poisson, renewal, or non-homogeneous Poisson. The simulation results show that the uniform random generation method is best among the three. These results are applied to actual field data collected for a subsystem of a certain type of guided missile to identify its failure process and to estimate its mean time to failure and annual mean repair cost

Joint Optimization of Redundancy and Component-Reliabilities in a Series System

Systems reliability can be improved by using redundancy and/or developing more reliable components. This paper considers a joint optimization of both alternatives for a series system. It is shown that the n-stage optimization problem can be decomposed into n single stage subproblems. Each subproblem is further transformed into a univariate optimization problem for which a simple and efficient solution method is developed

Development of a tabu search heuristic for solving multi-objective combinatorial problems with applications to constructing discrete optimal designs

Tabu search (TS) has been successfully applied for solving many complex combinatorial optimization problems in the areas of operations research and production control. However, TS is for single-objective problems in its present form. In this article, a TS-based heuristic is developed to determine Pareto-efficient solutions to a multi-objective combinatorial optimization problem. The developed algorithm is then applied to the discrete optimal design problem in statistics to demonstrate its usefulness

Determination of engineering characteristic values by quality function deployment

초록 The basic idea of Quality Function Deployment(QFD) is to deploy the voice of customers into the final product through product planning, part planning, process planning, and manufacturing. In the product planning stage, which is the first stage of product development, customer attributes(CAs) are translated into engineering characteristics(ECs). Then, based on the relationship between CAs and ECs, the target values of ECs are determined. In the previous research, the process of analyzing these relationships is mostly subjective in nature. In this article, we formulate the process of determining the target values of ECs as an optimization model. That is, we first determine the relationship between CAs and ECs as cumulative logit models and construct constraints into which the company strategy as well as the needs of customers can be incorprated. Next, cost functions of ECs are developed, which are summed into an objective function. An algorithm to solve the formulated optimization problem is developed and illustrated with an example