In Nigeria, Igbemo-Ekiti is synonymous with a popular local rice which, nevertheless, is characterized with contaminations. Efforts of Government through the Agricultural Development Project (ADP) to improve rice quality in the state, have failed to yield the desired results. This study, therefore, reports the peculiar factors influencing the processing of rice in Igbemo-a major local producing town in Ekiti State, Nigeria. 72 respondents were interviewed, which was a census of the rice processors in 21 residential quarters of the town. Using the multiple linear regression models for analysis, the study discovered that; (i) status of the processors, (ii) expenditure on processing (iii) training acquired before commencing work, and (iv) storage facilities are crucial factors impacting rice processing activities in the town. The paper canvasses for policy measures based on research findings.

This paper studies six different AHP (Analytic Hierarchy Process) approaches and suggests that the features of the approaches are classified by application circumstances in order to contribute to the applicability and quality usage of the AHP. Our study investigates the hierarchical principles and characteristics of the AHP, and historical debates on the AHP evaluation in which the six approaches have been involved. One of six approaches is an ANP (Analytic Network Process) application that is directly connected to AHP usage. The application differences among the six approaches are validated with a plain example. Then, the four circumstances of AHP applications are classified by two dimensions: the first dimension is whether or not the importance (weights) of criteria is independent of restrictively setting alternatives, and the second dimension is whether or not preference (priorities) of alternatives is independent of adding alternative(s) to or removing alternative(s) from the considering set of alternatives. Then featuring way of weighting criteria is classified. We suggest the distinguishing manners and describe the implications of the AHP application. Finally, we discuss rank reversal and multiplicative AHP.

We present a new integer programming formulation and a class of valid inequalities for solving the one-dimensional facility layout problem, which leads to a very efficient solution method for the problem.

This paper considers bandwidth allocation and scheduling problems on Ethernet Passive Optical Networks (EPON). EPON is one of the good candidates for the optical access network. This paper formulates the bandwidth allocation problem as a nonlinear mathematical one and characterizes the optimal bandwidth allocation which maximizes weighted sum of throughput and fairness. Based upon the characterization, two heuristic algorithms are suggested with various numerical tests. The test results show that our algorithms can be used for efficient bandwidth allocation on the EPON. This paper also shows that the WSPT (Weighted Shortest Processing Time) rule is optimal for minimization the total delay time in transmitting the traffic of the given allocated bandwidth.

Semi-supervised learning incorporates unlabeled examples, whose labels are unknown, as well as labeled examples into learning process. Although transductive support vector machine (TSVM), one of semi-supervised learning models, was proposed about a decade ago, its application to large-scaled data has still been limited due to its high computational complexity. Our previous research addressed this limitation by introducing a branch-and-bound algorithm for finding an optimal solution to TSVM. In this paper, we propose three new techniques to enhance the performance of the branch-and-bound algorithm. The first one tightens min-cut bound, one of two bounding strategies. Another technique exploits a graph-based approximation to a support vector machine problem to avoid the most time-consuming step. The last one tries to fix the labels of unlabeled examples whose labels can be obviously predicted based on labeled examples. Experimental results are presented which demonstrate that the proposed techniques can reduce drastically the number of subproblems and eventually computational time.

In this paper, we readdress the optimization problem for minimizing the inspection cost in a back-light unit inspection system, which forms a network including a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective function when the system is in a steady state, assuming that the number of nonconforming items in a lot follows a binomial distribution when a lot is formed for inspection, we make a steady-state network flow analysis between shops, and derive the steady-state amount of flows between nodes and the steady-state fraction defectives by solving a nonlinear balance equation. Finally we provide some fundamental properties and an enumeration method for determining an optimal value of K which minimizes our objective function. In addition, we compare our results numerically with previous ones.