Production scheduling which is a part of the planning and control of production units lies at the heart of the performance of manufacturing organizations. Production scheduling determines organizational performance. The need for efficient scheduling has greatly increased in recent decades owing to market demands for product quality, flexibility and order flow times, and other measures. However, although scheduling research activities have in the same period moved from purely academic exercises to serious attempts to solve practical problems in companies, successful implementations of scheduling techniques in practice are still scarce [1-6] and less attempt on solving the same from an economic perspective. In many companies, scheduling is still a typically human domain. However, the task of scheduling production units can become very complex. Humans are not very well equipped to barely control or optimize large and complex systems without computational tools, and the relations between actions and effects are difficult to assess. This paper will focus on problems that are related to the complexity of scheduling in practice. Scheduling based on this techniqueis often changed by the scheduler due to random disruptions or are not carried out exactly as preplanned on the shop floor. Because of the complex production processes, schedules are often difficult to assess mainly in terms of production cost. This paper takes a leap approach by assessing production performance in terms of cost. A new criterion of optimality is also proposed and used. This criterion is termed "total opportunity cost" and takes into account the different single criterion in a weighed term.
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