Decision Time
Mickey R. Wilhelm

Time is an artificial, universally accepted construct employed to standardize, mark or measure the occurrence of events. The innate sense of passing time, and the recognition that time is a fixed, non-renewable resource, prompts individuals to maximize their achievements - their productivity - during their brief lives.

Humans attempt to maximize goal attainment (e.g. quality of life, service, profit, etc.) by expending resources over time. But, productivity in goal-directed activity is measured as the ratio of output achieved to input of resources required, both functions of time, and the time constants for the numerator and denominator the ratio can be very different, (e.g., short-term investments in order to corner a market in the long-term.)

To maximize productivity, countless decisions must be made in a timely fashion, and, the granularity of input data needed to support the subsequent levels of decision-making must be considered. A typical process is that data gathered in time are filtered to yield information, which forms a knowledge base. Based on that knowledge, decisions are made and control actions formulated and implemented.

Complex databases at each stage can cause data/information overload in individuals and organizations. As a result, we use computers to mine, gather and filter data, and build knowledge bases. In theory, we can make intelligent, automated decision and control actions via hierarchical and heterarchical controllers that emulate human behavior. To cope with the "information explosion," these decision support systems manage time (reduce time the constants) to help individuals or organizations perform more productively by reducing the data stimulus-to-control response times.

Influential Readings

• Valckenaers, P., H. Van Brussel, J. Wyns, L. Bonagaerts, and P. Peeters, Designing Holonic Manufacturing Systems, Robotics and Computer-Integrated Manufacturing, 14 (1998) 455-464.
• McGinnis, L. F., M. Goetschalckx, G. Sharp, D. Bodner, and T. Govindaraj, Rethinking Warehouse Design Research, in Progress in Material Handling Research: 2000, co-editors R. J. Graves, L. M. McGinnis, M. K. Ogle, B. A Peters, R.E. Ward, and M. R. Wilhelm, The Material Handling Institute, Charlotte, NC, 2001.
• Heragu, S. S., R. J. Graves, B. Kim, and A. St. Onge, Intelligent Agent-Based Framework for Integrating Planning and Design in Material Handling Systems, in Progress in Material Handling Research: 2000, coeditors R. J. Graves, L. M. McGinnis, M. K. Ogle, B. A Peters, RE Ward, and M. R. Wilhelm, The Material Handling Institute, Charlotte, NC, 2001.
• Wilhelm, M. R., The Control of Material Handling Systems by Fuzzy Logic, in Progress in Material Handling Research: 1992, coeditors R. J. Graves, L. M. McGinnis, R. E. Ward, and M. R. Wilhelm, Braun-Brumfield Publishers, Ann Arbor, Michigan, 1993.