There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

An Introduction to MultiAgent Systems.

[서평]「The Unified Modeling Language User Guide」

https://homepages.fhv.at/hgb/New-Papers/CMAME07_BS07b.pdf

Robust Optimization - A Comprehensive Survey

https://ira.lib.polyu.edu.hk/bitstream/10397/1269/1/SetupSurvey-2006%28June-19%29.pdf

A survey of scheduling problems with setup times or costs

Many manufacturing facilities generate and update production schedules, which are plans that state when certain controllable activities (e.g., processing of jobs by resources) should take place. Production schedules help managers and supervisors coordinate activities to increase productivity and reduce operating costs. Because a manufacturing system is dynamic and unexpected events occur, rescheduling is necessary to update a production schedule when the state of the manufacturing system makes it infeasible. Rescheduling updates an existing production schedule in response to disruptions or other changes. Though many studies discuss rescheduling, there are no standard definitions or classification of the strategies, policies, and methods presented in the rescheduling literature. This paper presents definitions appropriate for most applications of rescheduling manufacturing systems and describes a framework for understanding rescheduling strategies, policies, and methods. This framework is based on a wide variety of experimental and practical approaches that have been described in the rescheduling literature. The paper also discusses studies that show how rescheduling affects the performance of a manufacturing system, and it concludes with a discussion of how understanding rescheduling can bring closer some aspects of scheduling theory and practice.

/pdf/rescheduling-manufacturing-systems-a-framework-of-strategies-2ihvpab9tj.pdf

Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods

Isr develops, applies and teaches advanced methodologies of design and analysis to solve complex, hierarchical, heterogeneous and dynamic problems of engineering technology and systems for industry and government. Isr is a permanent institute of the university of maryland, within the a. James clark school of engineering. It is a graduated national science foundation engineering research center. Abstract This paper surveys the contributions and applications of queuing theory in the field of healthcare. The paper summarizes a range of queuing theory results in the following areas: waiting time and utilization analysis, system design, and appointment systems. The paper also considers results for systems at different scales, including individual departments (or units), healthcare facilities, and regional healthcare systems. The goal is to provide sufficient information to analysts who are interested in using queuing theory to model a healthcare process and want to locate the details of relevant models.

A Survey of Queuing Theory Applications in Healthcare

Robust discrete optimization is a technique for structuring uncertainty in the decision-making process. The objective is to find a robust solution that has the best worst-case performance over a set of possible scenarios. However, this is a difficult optimization problem. This paper proposes a two-space genetic algorithm as a general technique to solve minimax optimization problems. This algorithm maintains two populations. The first population represents solutions. The second population represents scenarios. An individual in one population is evaluated with respect to the individuals in the other population. The populations evolve simultaneously, and they converge to a robust solution and its worst-case scenario. Since minimax optimization problems occur in many areas, the algorithm will have a wide variety of applications. To illustrate its potential, we use the two-space genetic algorithm to solve a parallel machine scheduling problem with uncertain processing times. Experimental results show that the two-space genetic algorithm can find robust solutions.

/pdf/a-genetic-algorithm-for-minimax-optimization-problems-2awpizm5ac.pdf

A genetic algorithm for minimax optimization problems

A History of Production Scheduling- The Human Factor in Planning and Scheduling- Organizational, Systems and Human Issues in Production Planning, Scheduling and Control- Decision-Making Systems in Production Scheduling- Scheduling and Simulation- Rescheduling Strategies, Policies, and Methods- A Practical View of the Complexity in Developing Master Production Schedules: Fundamentals, Examples, and Implementation- Coordination Issues in Supply Chain Planning and Scheduling- Semiconductor Manufacturing Scheduling and Dispatching- The Slab Design Problem in the Steel Industry- A Review of Long- and Short-Term Production Scheduling at Lkab's Kiruna Mine- Scheduling Models for Optimizing Human Performance and Well-Being

/pdf/handbook-of-production-scheduling-37srdhr898.pdf

Jeffrey W. Herrmann

Papers

Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods

A Survey of Queuing Theory Applications in Healthcare

A genetic algorithm for minimax optimization problems

Handbook of production scheduling

On scheduling to minimize earliness-tardiness and batch delivery costs with a common due date