We consider an $M^x/G/1$ queueing system with a random setup time under Bernoulli vacation schedule, where the service of the first unit at the completion of each busy period or a vacation period is preceded by a random setup time, on completion of which service starts. However, after each service completion, the server may take a vacation with probability p or remain in the system to provide next service, if any, with probability (1-p). This generalizes both the $M^x/G/1$ queueing system with a random setup time as well as the Bernoulli vacation model. We carryout an extensive analysis for the queue size distributions at various epochs. Further, attempts have been made to unify the results of related batch arrival vacation models.

This study compares the cycle times of handling operations of yard cranes under different sequencing rules. An operation cycle was divided into several elementary movements and formulas for the expectation and the variance of each elementary movement were analytically derived. The expected waiting time of trucks was estimated based on the given arrival rate of trucks. The previous studies focused on developing a method to make an efficient schedule of operations for yard cranes. This paper introduces several sequencing rules, such as first-come-first-served, unidirectional travel, and Z pick travel rules. In addition, a formula for estimating the cycle times of yard cranes under each sequencing rule is derived, and the performance under the different sequencing rules are compared with each other.

In this paper, we address a problem for minimizing the number of items inspected in a back-light-unit (BLU) inspection system, which includes a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective, we make a steady-state flow analysis between nodes (or shops), and derive the steady-state amount of flows between nodes and defective rates by solving a nonlinear balance equation. We provide an enumeration method for determining an optimal value of K which minimizes the number of items inspected. Our methodology could be applied and extended to similar situations with slight modification.

In this paper, we consider a relatively new two-machine flow shop scheduling problem where the unit time WIP cost increases as a job passes through various stages in the production process, and the objective is to minimize the total WIP (work-in-process) cost. Specifically, we study three special cases of the problem. First, we consider the problem where processing times on machine 1 are identical. Second, the problem with identical processing times on machine 2 is examined. The recognition version of the both problems is unary NP-complete (or NP-complete in strong sense). For each problem, we suggest two simple and intuitive heuristics and find the worst case bound on relative error. Third, we consider the problem where the processing time of a job on each machine is proportional to a base processing time. For this problem, we show that a known heuristic finds an optimal schedule.

In quantitative contexts, data mining is widely applied to the prediction of stock prices from financial time-series. However, few studies have examined the potential of data mining for shedding light on the qualitative problem-solving knowledge of experts who make stock price predictions. This paper presents a GA-based data mining approach to characterizing the qualitative knowledge of such experts, based on their observed predictions. This study is the first of its kind in the GA literature. The results indicate that this approach generates rules with higher accuracy and greater coverage than inductive learning methods or neural networks. They also indicate considerable agreement between the GA method and expert problem-solving approaches. Therefore, the proposed method offers a suitable tool for eliciting and representing expert decision rules, and thus constitutes an effective means of predicting the stock price index.

The minimum multicut problem on a cycle is to find a multicut on an undirected cycle such that the sum of weights is minimized, which is known to be polynomially solvable. This paper shows that there exists a compact polyhedral description of the set of feasible solutions to the problem whose number of variables and constraints is O($\upsilon\kappa$).