FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION：THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturingscheduling and supply chain coordination are critical to quickly respond to changing marketconditions. These problems, however, are difficult in view of inherent complexity and variousuncertainties involved. Based on a series of results by the authors, decomposition and coordination byusing Lagrangian relaxation is identified in this paper as an effective way to control complexity anduncertainty.A manufacturing scheduling problem is first formulated within the job shop context withuncertain order arrivals, processing times, due dates, and part priorities as a separable optimizationproblem. A solution methodology that combines Lagrangian relaxation, stochastic dynamicprogramming, and heuristics is developed. Method improvements to effectively solve large problemsare also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomicmembers across chains of suppliers, a decentralized supply chai     

Analysis of discrete-time queues with batch renewal input and multiple vacations

This paper analyzes a discrete-time multiple vacations finite-buffer queueing system with batch renewal input in which inter-arrival time of batches are arbitrarily distributed.Service and vacation times are mutually independent and geometrically distributed.The server takes vacations when the system does not have any waiting jobs at a service completion epoch or a vacation completion epoch.The system is analyzed under the assumptions of late arrival system with delayed access and early arrival system.Using the supplementary variable and the imbedded Markov chain techniques, the authors obtain the queue-length distributions at pre-arrival,arbitrary and outside observer’s observation epochs for partial-batch rejection policy.The blocking probability of the first-,an arbitrary-and the last-job in a batch have been discussed.The analysis of actual waiting-time distributions measured in slots of the first-,an arbitrary- and the last-job in an accepted batch,and other performance measures along with some numerical results have also been investigated.     

Suggestions for New Application Areas for Soft Systems Methodology in the Information Age

Soft systems methodology (SSM) is now 40?years old. Another decade has passed since Checkland??s thirty year retrospective on the methodology, published in 2000. It can now be described as an old methodology. But it has adapted and changed over the years and is still very much alive, although the days are long gone when it was mainly developed and practised by its founders at the University of Lancaster. Interestingly, considering that many applications of SSM over the years have been to information systems, it was developed before the age of personal computers and the Internet. The way SSM is viewed has changed over the years as it has been applied to various types of problem situation. Every use of SSM will potentially hold methodological lessons in addition to those about the situation of concern; these may include SSMs framework of ideas, processes and way of use. How is SSM going to change in the future? This will depend in part on the types of problem situation to which it is applied. This paper examines some problem situations associated with emerging technologies in the information age to which SSM has not yet been much applied. These include computer simulation and virtual reality, ubiquitous computing and the design of cities, Information Technology Service Management and the design of enterprise information architectures. Some of the different worldviews associated with these problem situations which could be explored using SSM are noted.     

An equivalency condition of nonsingularity in nonlinear semidefinite programming

<正> In this paper,an equivalency condition of nonsingularity in nonlinear semidefinite programming,which can be viewed as a generalization of the equivalency condition of nonsingularity for linearsemidefinite programming,is established under certain conditions of convexity.     

MULTIPLE CRITERIA DECISION MAKING： DISCORDANT PREFERENCES AND PROBLEM DESCRIPTION

There are many practical decision problems where decision makers＇ preferences may be inconsistent and contradictory. In this paper, new methods for ordering and classifying multi-attribute objects by discordant collective preferences are suggested. These methods are based on the theory of multiset metric spaces. The proposed techniques are applied to ranking companies and a competitive selection of projects, which are estimated by several experts upon multiple qualitative criteria.     

Creating Action Research Quality in Organization Development: Rigorous,Reflective and Relevant

The purpose of the paper is to present a framework that enables action researchers to create quality action research projects within the organization development (OD) domain using the broad criteria of being rigorous, reflective and relevant and so contribute to the realm of practical knowing. What constitutes good quality action research within OD is a difficult question, given the broad range of approaches that operates in a wide variety of settings and with great diversity. It advances specific dimensions by which action researchers can create, review and assess quality in action research work. This integrative framework and criteria are practical tools to enable action researchers to create quality action research in OD.     

Termination of asymmetric cell division and differentiation of stomata

Stomata consist of a pair of guard cells that mediate gas and water-vapour exchange between plants and the atmosphere. Stomatal precursor cells-meristemoids-possess a transient stem-cell-like property and undergo several rounds of asymmetric divisions before further differentiation. Here we report that the Arabidopsis thaliana basic helix-loop-helix (bHLH) protein MUTE is a key switch for meristemoid fate transition. In the absence of MUTE, meristemoids abort after excessive asymmetric divisions and fail to differentiate stomata. Constitutive overexpression of MUTE directs the entire epidermis to adopt guard cell identity. MUTE has two paralogues: FAMA, a regulator of guard cell morphogenesis, and SPEECHLESS (SPCH). We show that SPCH directs the first asymmetric division that initiates stomatal lineage. Together, SPCH, MUTE and FAMA bHLH proteins control stomatal development at three consecutive steps: initiation, meristemoid differentiation and guard cell morphogenesis. Our findings highlight the roles of closely related bHLHs in cell type differentiation in plants and animals.     

Classification and Categorical Inputs with Treed Gaussian Process Models

Recognizing the successes of treed Gaussian process (TGP) models as an interpretable and thrifty model for nonparametric regression, we seek to extend the model to classification. Both treed models and Gaussian processes (GPs) have, separately, enjoyed great success in application to classification problems. An example of the former is Bayesian CART. In the latter, real-valued GP output may be utilized for classification via latent variables, which provide classification rules by means of a softmax function. We formulate a Bayesian model averaging scheme to combine these two models and describe a Monte Carlo method for sampling from the full posterior distribution with joint proposals for the tree topology and the GP parameters corresponding to latent variables at the leaves. We concentrate on efficient sampling of the latent variables, which is important to obtain good mixing in the expanded parameter space. The tree structure is particularly helpful for this task and also for developing an efficient scheme for handling categorical predictors, which commonly arise in classification problems. Our proposed classification TGP (CTGP) methodology is illustrated on a collection of synthetic and real data sets. We assess performance relative to existing methods and thereby show how CTGP is highly flexible, offers tractable inference, produces rules that are easy to interpret, and performs well out of sample.