A Conceptual “Cybernetic” Methodology for Organizing and Managing the E-Learning Process through [D-] CIVEs

This chapter presents a conceptual-pedagogical “cybernetic” methodology for cyber entities’ (avatars’) spatial awareness, in an innovative way by using Second Life (SL). According to this section, it’s crucial to answer the major question of how teachers can permit effective actions through the organizational complexity of virtual and technical interactions that SL governs, making it more practical for Higher Education. Additionally, the chapter’s objective emphasizes the creation of an organizational-educational (multi-) method, which is essential for effective planning and conducting in distance learning programs. Furthermore, the construction effort is based on Anthony Stafford Beer’s “Viable System Model” (VSM) principal characteristics, in which the chapter contends the pedagogical analysis of teaching and didactic process that should be supported by any “open,” “viable,” and “sustainable” virtual learning environment. The systematic description and classification of groups’ interaction scripts aim is to help facilitating and enhancing teams’ knowledge management by providing reusable patterns that leverage the ample possibilities.

A New Modeling and Application of Hierarchical Production Planning Approach

In real power systems, power plants are not in the equal space from the load center, and their fuel cost is different. With common utilization conditions, production capacity is more than total load demand and losses. Therefore, there are different criteria for active and inactive power planning in each power plant. The best selection is to choose a framework in which the utility cost is minimized. On the other hand, planning in power systems has different time horizons; thus, for effective planning in power systems, it is very important to find a suitable mathematical relationship between them. In this chapter, the authors propose a modeling by selecting a Fuzzy Hierarchical Production Planning (FHPP) technique with zone covering in the mid-term and long-term time horizons electricity supply modeling in the Iran global compact network.

Production and Inter-Facility Transportation with Shipment Size Restrictions

This chapter studies production and transportation problem confronting a speciality chemical company that has two manufacturing facilities. Facility I produces intermediate products which are then transported to Facility II where the end products are to be manufactured to meet customers’ demand. The author formulated the problem as a mixed integer programming (MIP) model that integrates the production and transportation decisions between the two facilities. The developed MIP aims to minimize the production, inventory, manpower, and transportation costs. Real industrial data are used to test and validate the developed MIP model. Comparing the model’s results and the company’s actual performance indicate that, if the company implemented the proposed model, significant costs savings could be achieved.

Alternative Approaches to Auction Trading by Consortia in Multi Agent Systems

Agent-based auction trading is important in e-Procurement as a part of the supply chain management activity of procurement via the Internet. Participating buyers and sellers are intelligent agents tasked with finding matches with required or offered quantities for best performance. Formation of consortiums offers opportunities in matching trade volumes, but in the real world, there are difficulties in optimizing consortium formation due to lack of perfect information and the dynamic character of the information. Heuristic methods are often the only solution. This chapter shows the impact and capabilities of alternate heuristic models, and compares their performances in auction trading.

Towards a Beneficial Formalization of Cyber Entities’ Interactions during the E-Learning Process in the Virtual World of “Second Life”

This chapter investigates the new interactive dimension, which arises between cyber entities (avatars) that move around, meet others, and emulate their work in [D-] CIVEs ([Distributed-] Collaborative Immersive Virtual Environments). The active involvement and immersion in these “environments” elaborates the maximum possible total-relationship of the developmental users’ forces (teachers and students) and creates “situations of real-life” in a 3D virtual system. The inspiration to deal with this issue originated through the prior knowledge that was gained from the previous educational studies in the virtual world of Second Life (SL), which was used as an environmental tool for action-based learning and research programs on Higher Education. The investigation and presentation of quality infrastructure that this interactive “world” hosts in was the objective of this research, through the presentation and promotion of academic communities’ previous applications to enrich their curricula. The original contribution of this effort is to become a highly inexhaustible source of inspiration for the bibliographic data and interdisciplinary for the field of e-learning future.

Design of Robust Supply Chains

In a supply chain operating under uncertainty, a possible approach to reduce the complexity and scope of the planning process is to organize all involved critical planning decisions in a hierarchical structure. This chapter attempts to explore new ways of integrating production and scheduling plans in a complex supply chain taking into account effects of some specific uncertainty types. In particular, uncertainty types inherent to the demand and to the process or equipment are considered. To deal with demand uncertainty at the strategic level, the safety stock placement problem in supply chains with limited production capacities is investigated. Results of this analysis and its consequences at the design level are reported and discussed. At the tactical level, each stage in the supply chain generates its own aggregate plans in order to balance supply and demand. To deal with uncertainty at this level, some robust deterministic planning models are discussed. These models make use only of the readily available data, such as averages and standard deviations, related to the uncertain planning parameters. At the operational level, the issue of disaggregating the generated robust tactical plans into detailed plans is investigated. A model taking into account the progressive deterioration of the production equipment is discussed. The results of some simulations are also reported and discussed.

A Multi-Agent System for Production Networks Simulation

In this chapter, the authors present a multi-agent model aimed to investigate emergent organizational structures in production networks and their reification by means of pheromone-based algorithms. The model considers agents (firms) embedded in a production network, interacting among them through business-to-business relations. The evolution of the network structure is endogenous, as it takes into account the individual behavior of the firms and their interactions. The firms are adaptive agents taking investment decisions according to their business efficiency. They adapt their prices to be competitive and get a larger share of the market. Also, they adapt their business relations with their suppliers in order to reduce costs of inputs and get orders satisfied. The agent’s proactivity, with very simple decision mechanisms at the micro level, leads to the emergence of meta-stable business clusters and supply chains at the macro level. Pheromone-based algorithms reify dynamically these clusters as explicit graphs. The results of the authors’ simulations show the impact of the transportation cost and the geographical reach on the regionalization of production and on wealth patterns. Individual firms, with local B2B interactions and decisions, form stable production systems based on the supply/demand and market growth mechanisms leading to the maturation of the market.

Agent-Based Modeling and Simulation of Intelligent Distributed Scheduling Systems

For responsiveness and agility, disruptive events must be managed locally to avoid propagating the effects along the value chain. In this work, a novel approach based on emergent distributed scheduling is proposed to overcome the traditional separation between task scheduling and execution control. An interaction mechanism designed around the concept of order and resource agents acting as autonomic managers is described. The proposed Manufacturing Execution System (MES) for simultaneous distributed (re)scheduling and local execution control is able to reject disturbances and successfully handle unforeseen events by autonomic agents implementing the monitor-analyze-plan-execution loop while achieving their corresponding goals. For detailed design of the autonomic MES and verification of its emergent behaviors, a goal-oriented methodology for designing interactions is proposed. Encouraging results obtained for different operating scenarios using a generative simulation model of the interaction mechanism implemented in Netlogo are presented.

Measures of Risk on Variability with Application in Stochastic Activity Networks

The author proposes a simple measure of variability of some of the more commonly used distribution functions in the class of New-Better-than-Used in Expectation (NBUE). The measure result in a ranking of the distributions, and the methodology used is applicable to other distributions in NBUE class beside the one treated here. An application to stochastic activity networks is given to illustrate the idea and the applicability of the proposed measure.

Distributed Production Planning Models in Production Networks

Production networks can be dynamically structured and involving multiple production sites with different objectives. This organizational structure is able to match agility and efficiency to compete in the global market. In this environment is impossible for a single organization to control whole production networks; thus, a decentralized approach has been developed to manage the production networks. However, the coordinate mechanism in decentralized control is more important to obtain a high level of performance. The research proposes innovative coordination strategies for coordinate production networks by Multi Agent Architecture. A link between negotiation strategies and a production planning algorithm has been developed in order to support the coordination strategies proposed. In particular, two protocols to reach an agreement between customer and the production network have been proposed: negotiation and an expected profit approaches. Moreover, two coordination strategies have been proposed: index efficiency and ranking price approaches. Finally, the possibility of divide the orders in lots by the customer is proposed. A simulation environment based on open source code and Multi Agent Architecture has been developed to test the proposed approaches. The experiments have been conducted in different conditions of workload and mar-up; the results of the simulation provide the information necessary to select the suitable coordination and protocol mechanisms in a distributed production planning problem.