The rapid changing business environment of high-tech asset intensive enterprises such as semiconductor manufacturing constantly drives production managers to look for better solutions to improve the manufacturing process. Simulation, though identified to be the most appropriate technique to generate and test out possible execution plans, suffers from long cycle-time in the process of model update, analysis and verification. It is thus very difficult to carry out prompt "what-if" analysis to respond to abrupt changes in these systems. Symbiotic simulation systems have been proposed as a way of solving this problem by having the simulation and the physical system interact in a mutually beneficial manner. In this paper, we describe our work in developing a prototype proof-of-concept symbiotic simulation system that employs software agents in the monitoring, optimization and control of a semiconductor assembly and test operation.

This paper addresses some difficulties common in planning and scheduling work in the MRO industries. We present a solution developed based on Microsoft Project Server for managing and optimizing the deployment of critical resources so as to maximize the project profits. We discuss the methods for managing of multiple projects based on enterprise shared resources, identifying the critical chain for multiple projects, and optimizing their makespans and costs with constrained resources using overtime and outsourcing strategies. We present some results to show the viability and efficiency of the solution in an MRO environment. Several potential research issues are identified and discussed for future research.

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This paper presents an evolutionary algorithm to develop cooperative strategies for power buyers in a deregulated electrical power market. Cooperative strategies are evolved through the collaboration of the buyer with other buyers defined by the different group memberships. The paper explores how buyers can lower their costs by using the algorithm that evolves their group sizes and memberships. The algorithm interfaces with PowerWorld Simulator to include in the technical aspect of a power system network, particularly the effects of the network constraints on the power flow. Simulation tests on an IEEE 14-bus transmission network are conducted and power buyer strategies are observed and analyzed.

In this paper, we present how a solution framework developed for (a special case of) the multi-objective simulationoptimization problems can be applied to evaluate and optimally select the non-dominated set of inventory policies for two case study problems. Based on the concept of Pareto optimality, the solution framework mainly includes how to evaluate the quality of the selected Pareto set by two types of errors, and how to allocate the simulation replications according to some asymptotic allocation rules. Given a fixed set of inventory policies for both case study problems, the proposed solution method is applied to allocate the simulation replications. Results show that the solution framework is efficient and robust in terms of the total number of simulation replications needed to find the nondominated Pareto set of inventory policies.