Asia-Pacific Journal of Operational Research

We introduce a method for maximizing the run-out time for a system where the number of components available to make repairs is finite, and some of the components may be substituted for one another. The objective is to maximize the time at which the earliest run-out of any component occurs. The approach proposed here is to find the minimum time horizon such that no feasible allocation exists for a related linear programming problem. An adaptive version of this algorithm is proposed as a heuristic for the stochastic problem.

It is an important problem to determine the tenuring collection time or major collection time to meet the pause time goal for a generational garbage collector. From such a viewpoint, this paper proposes two stochastic models based on the working schemes of a generational garbage collector: Garbage collections occur at a nonhomogeneous Poisson process. Minor collections are made when the garbage collector begins to work, tenuring collection is made at a planned time T or at the first collection time when surviving objects have exceeded K for the first model. Major collection is made at time T or at the Nth collection for the second model. Using the techniques of cumulative processes and reliability theory, expected cost rates are obtained, and optimal policies of tenuring and major collection times which minimize them are discussed analytically and computed numerically.

Optimal release time determination is a typical application of software reliability models. In this decision process, reliability and cost are the two important dimensions that are generally considered. Most existing research formulates this decision process as single-objective optimization problems. Although these formulations can greatly reduce the complexity, they can hardly reflect the nature of the decision process, which is essentially a multi-objective optimization problem. More specifically, maximizing reliability and minimizing cost should be achieved simultaneously. Due to this consideration, in this paper, software release time determination is investigated by various multi-objective optimization approaches, including the trade-off analysis, multi-attribute utility theory, and physical programming approach. Numerical examples are provided for illustrative purpose. The applicability and limitations of different multi-objective optimization approaches are also discussed, which can help management to make a more reasonable decision in practice.

This paper presents the effects of a free minimal repair warranty (FMRW) on the periodic replacement policy under discrete operating circumstance. For the discrete-time periodic replacement policy, a product is preventively replaced at pre-specified operation cycles N, 2N, 3N, … (N = 1, 2, …). When the product fails, a minimal repair is performed at the time of failure and the failure rate is not disturbed by each repair. From the customer's perspective, the cost models are developed for both a warranted and a nonwarranted product, and the corresponding optimal periodic replacement policies are derived such that the long-run expected cost rates are minimized. Under the assumption of the discrete time increasing failure rate (IFR), the existence and uniqueness of the optimal N* are shown, and the impacts of a FMRW on the optimal replacement policies are investigated analytically. We found that the optimal N* for a warranted product should be adjusted toward the end of the warranty period.

This paper proposes a performance index to evaluate the capability of a maintainable computer network (MCN) that is required to send d units of data from the source to the sink through two paths within time T. The proposed system reliability performance index quantifies the probability that a MCN delivers a sufficient capacity with a maintenance budget no greater than B. Two procedures are integrated in the algorithm — an estimation procedure for estimated system reliability and an adjusting procedure utilizing the branch-and-bound approach for accurate system reliability. Subsequently, the estimated system reliability with lower bound and upper bound, and accurate system reliability can be derived by applying the recursive sum of disjoint products (RSDP) algorithm.

For a repairable product that fails under warranty, the manufacturer can choose between repair and replacement. Many different warranty servicing strategies involving these two types of rectification action have already been studied. In this paper, we propose two new servicing strategies involving minimal repair, each with two parameters that are selected optimally to minimize expected warranty servicing costs. We develop models to obtain the optimal parameter values for each new strategy and then carry out a comparison with a selection of the existing strategies through a numerical example.

Reducing warranty servicing costs are of great interest to product manufacturers or sellers who are contractually bound to provide post-sales support, up to a specified warranty period, usually in the form of some remedial action that restores a failed item to a functioning condition. Here, in the spirit of Jack et al. (2009) strategy based on partitioning the effective warranty period into three intervals, we consider and analyze the cost of a new two-dimensional warranty servicing strategy, that probabilistically exercises a choice between a replacement and a minimal repair to rectify the first failure if any, in the middle interval. The behavior of the expected cost is numerical illustration with Weibull failure model.

Service availability is one of the customer-oriented attribute and defined as the attribute that the system can successfully satisfy the customers' requests. This paper discusses the stochastic service availability measurement for the computer-based system incorporating the concept of hardware/software codesign. We assume that the computer-based system consists of one hardware subsystem and one software subsystem and consider the situation where one customer intermittently uses the system which is operating and available anytime. From the viewpoint of a customer, occurrence of a system failure is recognized when either one of the following two events arises: A system failure occurs when the customer is using the system, or a usage request occurs when the system is down. We propose and derive three kinds of novel service-oriented system availability assessment measure. These are given as the functions of time and the number of software debuggings. The time-dependent behaviors of the system alternating between up and down states and the customer's request are described by a Markov process. Especially for the software subsystem, we incorporate the dynamic software reliability growth process, the upward tendency of difficulty in debugging, and the imperfect debugging environment into the model. Finally, we present several numerical examples of these measures for system service availability analysis.