Ant Colonies for Performance Optimization of Multi-components Systems Subject to Random Failures

Reliability has been considered as an important design measure in industry. The design of a system involves in general numerous discrete choices among available component types based on reliability, cost, performance, weight, etc. If the design objective is to maximize reliability for a certain cost requirement, then a strategy is required to identify the optimal combination of components and/or design configuration. This leads to combinatorial optimization problems which are NP-hard. For large industrial problems, exact methods are lacking since they require a very large amount of computation time to obtain the solution of the problem. This chapter will focus on the use of ant colonies to solve three optimal design problems which are among the most important in practice: 1. The reliability optimization of series systems with multiple-choice constraints incorporated at each subsystem, to maximize the system reliability subject to the system budget. This is a nonlinear binary integer programming problem and characterized as an NP-hard problem. 2. The redundancy allocation problem (RAP) of binary series-parallel systems. This is a well known NP-hard problem which involves the selection of elements and redundancy levels to maximize system reliability given various system-level constraints. As telecommunications and internet protocol networks, manufacturing and power systems are becoming more and more complex, while requiring short developments schedules and very high reliability, it is becoming increasingly important to develop efficient solutions to the RAP. 3. Buffers and machines selections in unreliable series-parallel production lines: we consider a series-parallel manufacturing production line, where redundant machines and in-process buffers are included to achieve a greater production rate. The objective is to maximize production rate subject to a total cost constraint. Machines and buffers are chosen from a list of products available in the market. The buffers are characterized by their cost and size. The machines are characterized by their cost, failure rate, repair rate and processing time. To estimate series-parallel production line performance, an analytical decomposition-type approximation is proposed. Simulation results show that this approximate technique is very accurate. The optimal design problem is formulated