Asia-Pacific Journal of Operational Research

In this note, a fuzzy inventory model with multiple items is considered. Economic order quantities (EOQs) are developed for these items. The costs involved in inventory are always assumed to be exact, otherwise called as crisp or hard, but in practice these costs are not exact or precise but vary over a range. In such cases an application of fuzzy set theory plays a vital role in obtaining the EOQ. An application of this model to manpower planning is studied with an example; sensitivity analysis is also made.

The multiprocessor scheduling problem with communication delays that we consider in this paper consists of finding a static schedule of an arbitrary task graph onto a homogeneous multiprocessor system, such that the total execution time (i.e. the time when all tasks are completed) is minimum. The task graph contains precedence relations as well as communication delays (or data transferring time) between tasks if they are executed on different processors. The multiprocessor architecture is assumed to contain identical processors connected in an arbitrary way, which is defined by a symmetric matrix containing minimum distances between every two processors. The solution is represented by a feasible permutation of tasks. In order to obtain the objective function value (i.e. schedule length, makespan), the feasible permutation has to be transformed into the actual schedule by the use of some heuristic method. For solving this NP-hard problem, we develop basic tabu search and variable neighborhood search heuristics, where various types of reduced Or-opt-like neighborhood structures are used for local search. A genetic search approach based on the same solution space is also developed. Comparative computational results on random graphs with up to 500 tasks and 8 processors are reported. On average, it appears that variable neighborhood search outperforms the other metaheuristics. In addition, a detailed performance analysis of both the proposed solution representation and heuristic methods is presented.

This paper focuses on the performance analysis on a complex remanufacturing system that consists of a disassembling shop, a remanufacturing shop, an assembling shop, and a warehouse. The optimal remanufacturing policy is given. Furthermore, by the matrix-geometric method, the immediate demand fill rate is established.

Financial Ratio Analysis is newly proposed to examine the financial performance of the American power/energy industry. The new approach compares the financial performances of 147 non-default firms with those of 24 default firms in the US power/energy market. The proposed approach is a new type of nonparametric discriminant analysis that provides a set of weights of a linear discriminant function, consequently yielding an evaluation score for group membership. Such weight estimates, along with an evaluation score, of the discriminant function provide a total financial evaluation measure, based upon which we can determine the financial performance of the power/energy firms. This empirical study informs that both leverage (debt) and profitability (returns on equity) are important financial factors in terms of avoiding corporate distress or bankruptcy. The empirical results obtained from the American power/energy industry are further extended to the international comparison of other major industrial nations including Japan and the European nations. The international comparison concludes that Japanese electric power firms have enough managerial and financial capabilities even if the American financial standard is hypothetically introduced into the evaluation of their financial performances. However, the empirical results also indicate that the Japanese power industry performs barely above the American standard. Thus, corporate leaders in the Japanese power industry need to pay more serious attention to their corporate finances and financial strategies. Such financial perspective will be increasingly important along with the current deregulation policy of the Japanese government.

We discuss the harvesting of a single forest block from an operations scheduling viewpoint. We report on a harvesting case study, based on practical data from a commercial enterprise, involving minimum and maximum time lags and resource constraints. It appears that the scheduling of the harvesting forest blocks is a significantly different scenario from those represented by the scheduling models available in the literature. The differences come about because: the duration of each operation is dependent upon the combination of constrained resources allocated to it, individual worker-equipment allocation is restricted, and minimum or maximum time lags can be imposed. We report on harvesting operations, a scheduling model, and solution procedures, designed specifically for the case study.

The purpose of this study is to present a simple lower bound to facilitate the development of branch-and-bound algorithms for the minimization of total completion time in a two-machine flowshop. The studied problem is known to be strongly NP-hard. In the literature, several lower bounds have been proposed. The bounding technique addressed in this paper is based upon a concept about rearrangement of the parameters of the input instance. The technique is intrinsically simple for computer implementations. We conduct computational experiments for problems with 10–65 jobs. Numerical results from our computational study indicate that the new scheme is very effective in reducing the execution time needed for composing optimal solutions.

In this paper, we consider a two-server finite capacity queuing model in which messages should leave the system in the order in which they entered the system. Messages arrive according to a Markovian arrival process (MAP) and any message finding the buffer full is considered lost. Out-of-sequence messages are stored in a (finite) buffer and may lead to blocking when a processed message cannot be placed in the buffer. The steady state analysis of the model is performed by exploiting the structure of the coefficient matrices. The departure process is characterized and two interesting optimization problems along with illustrative numerical examples are discussed.