基于能力拍卖和多Agent的综合生产计划分布式建模及求解

把拍卖和市场理念引入到生产计划的求解过程中,结合多Agent理论,对大规模生产系统按生产单元建立分布式模型.各个生产单元看作相对独立核算的经济实体,其目标是实现自身利益最大化.当生产能力足够时,按照需求进行生产;当生产能力不足以完全满足需求时,紧缺生产资源的持有者按照单位能力获得最大收益的原则进行生产竞价与拍卖,实现了各个生产单元的分布式自主协商决策,并设计了求解算法.算例研究证明该方法的可操作性和求解的有效性.     

Symmetric BEM formulations for 2-D steady-state and transit potential problems

This paper presents a new concept for symmetric boundary element method (SBEM) applicable to 2-D steady-state and transit potential problems. Two kinds of SBEM formulations are derived. Symmetry is obtained simply through matrix manipulation, and no hypersingularity appears. Therefore, SBEM is much easier than the traditional symmetric Galerkin BEM. Compared with the traditional asymmetric BEM, the present SBEM can reduce the computational cost for time domain problems only. However, when applied to BEM/FEM coupling procedure, SBEM can reduce the computational cost for both steady-state and time domain problems. Three numerical examples are included to illustrate the effectiveness and accuracy of the present formulations.     

Personality and the predisposition to engage in risky or problem behaviors during adolescence.

Longitudinal data from a representative sample of 1,978 Black and White adolescents were used to examine the role of personality in multiple risk or problem behaviors. Results indicate that covariation among diverse behaviors (educational underachievement, delinquent behavior, substance use, sexual behavior) can be adequately modeled by a single higher order factor, and that impulsivity and avoidance coping serve as generalized risk factors for involvement in these behaviors. Whereas none of the personality variables examined explained change in problem behaviors once established, avoidance coping prospectively predicted involvement among a subgroup of adolescents with little or no prior involvement. Results suggest that dysfunctional styles of regulating emotions and emotionally driven behaviors are core features of risky or problem behaviors during adolescence. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Line balancing in a just-in-time production environment: balancing multiple U-lines

The introduction of multiple, independent production lines has helped many firms to increase their production flexibility, provide for redundancy when equipment breaks down, reduce idle time and labor costs, and achieve many other benefits. This paper introduces and formalizes the multiple U-line balancing problem. Optimal solution methodologies are provided for Type I (minimize the number of stations for a given cycle time), Type II (minimize the cycle time for a given number of stations), and cost-minimization line-balancing problems. A branch-and-bound algorithm is also developed for the situation in which equipment requirements are dependent on the line configuration and the task assignment to stations. Computational results indicate that the greatest benefit of exploiting multiple lines occurs for smaller cycle-time problems that require higher output.     

Global Level Path Planning for Mobile Robots in Dynamic Environments

This paper presents a self-adapting approach to global level path planning in dynamic environments. The aim of this work is to minimize risk and delays in possible applications of mobile robots (e.g., in industrial processes). We introduce a hybrid system that uses case-based reasoning as well as grid-based maps for decision-making. Maps are used to suggest several alternative paths between specific start and goal point. The casebase stores these solutions and remembers their characteristics. Environment representation and casebase design are discussed. To solve the problem of exploration vs. exploitation, a decision-making strategy is proposed that is based on the irreversibility of decisions. Forgetting strategies are discussed and evaluated in the context of case-based maintenance. The adaptability of the system is evaluated in a domain based on real sensor data with simulated occupancy probabilities. Forgetting strategies and decision-making strategies are evaluated in simulated environments. Experiments show that a robot is able to adapt in dynamic environments and can learn to use paths that are less risky to follow.     

Strategic appraisal of energy models for Mozambique

The needs that an energy supply system must meet are constantly changing, due to technological, social and political reasons. Effective energy planning is a dynamic process that is repeated periodically and adjusts to changing conditions. Energy decision makers and planners are no longer able to rely on inductive decision making since they have to investigate the effect of various decision parameters and possible future changes. To help in this process, models have been developed where estimates of future load growth, candidate power plants, fuels and other key factors can be introduced, from which the planners can evaluate decision parameters and the available alternatives. The paper presents the different methodologies and practices that are used by 11 energy models for energy demand forecasting, supply side management and generation expansion planning, demand side management and integrated resource planning. The paper concludes to the presentation of a strategic appraisal of the examined energy models appropriate for energy planning in Mozambique. Three models are proposed for conducting demand forecasting, generation expansion planning and demand side management. Copyright © 2002 John Wiley & Sons, Ltd.     

国有施工企业走向市场应关注的几个问题

从辩证关系角度详细阐述了类似于北京燕化建筑工程公司这样的国有施工企业走向市场过程中应关注的企业定位、利益相关性、竞争策略与公平性、自我保护与內涵发展等问题,以促进国有施工企业的改革与发展。     

多部件设备维修问题研究及遗传算法求解

合理组织设备维修，缩短设备维修时间是生产运营管理的一个重要环节。本文探讨了多部件设备维修的有效组织问题。考虑到维修工人对拆分后设备的不同部分具有不同的维修效率，提出了一种基于维修时间优化的决策方法，将其与经典指派方法进行了比较；进一步地，对这一NP-hard问题设计了遗传算法，通过数值例子讨论了其求解有效性。     

Targeting optimum resource allocation using reverse problem formulations and property clustering techniques

Decoupling the constitutive equations from the balance and constraint equations allows for reformulating a conventional forward problem into two reverse problems. The first reverse problem is the reverse of a simulation problem, where the process model is solved in terms of the constitutive (synthesis/design) variables instead of the process variables, thus providing the synthesis/design targets. The second reverse problem (reverse property prediction) solves the constitutive equations to identify unit operations, operating conditions and/or products by matching the synthesis/design targets. Visualization of the problem is achieved by employing recently developed property clustering techniques, which allows a high-dimensional problem to be visualized in two or three dimensions. The clusters by definition satisfy intra-stream and inter-stream conservation through linear “mixing” rules, which allows for the development of consistent additive rules along with their ternary representation.     

Text planning with opportunistic control

This report describes the current state of our central research thrust in the area of natural language generation. We have already reported on our text-level theory of lexical selection in natural language generation ([59, 60]), on a unification-based syntactic processor for syntactic generation ([73]) and designed a relatively flexible blackboard-oriented architecture for integrating these and other types of processing activities in generation ([60]). We have implemented these ideas in our prototype generator, Diogenes — a DIstributed, Opportunistic GENEration System — and tested our lexical selection and syntactic generation modules in a comprehensive natural language processing project — the KBMT-89 machine translation system ([15]). At this stage we are developing a more comprehensive Diogenes system, concentrating on both the theoretical and the system-building aspects of a) formulating a more comprehensive theory of distributed natural language generation; b) extending current theories of text organization as they pertain to the task of planning natural language texts; c) improving and extending the knowledge representation and the actual body of background knowledge (both domain and discourse/pragmatic) required for comprehensive text planning; d) designing and implementing algorithms for dynamic realization of text structure and integrating them into the blackboard style of communication and control; e) designing and implementing control algorithms for distributed text planning and realization. In this document we describe our ideas concerning opportunistic control for a natural language generation planner and present a research and development plan for the Diogenes project.Many people have contributed to the design and development of the Diogenes generation system over the last four years, especially Eric Nyberg, Rita McCardell, Donna Gates, Christine Defrise, John Leavitt, Scott Huffman, Ed Kenschaft and Philip Werner. Eric Nyberg and Masaru Tomita have created genkit, which is used as the syntactic component of Diogenes. A short version of this article appeared in Proceedings of IJCAI-89, co-authored with Victor Lesser and Eric Nyberg. To all the above many thanks. The remaining errors are the responsibility of this author.