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Multi-objective formulations are realistic models for many complex engineering optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a(More)
& Conclusions-A problem specific genetic algorithm (GA) is developed and demonstrated to analyze series-parallel systems and to determine the optimal design configuration when there are multiple component choices available for each of several k-out-of-n:G subsystems. The problem is to select components and levels of redundancy to optimize some objective(More)
—This paper presents a genetic algorithm (GA) with specialized encoding, initialization, and local search operators to optimize the design of communication network topologies. This NP-hard problem is often highly constrained so that random ini-tialization and standard genetic operators usually generate infea-sible networks. Another complication is that the(More)
Scope and Purpose There are a vast number of practical design and resource-allocation problems, in many different fields, where the decision to be made is a matching (or assignment) of items in one set to items in another, disjoint set. If the costs associated are simply constants for each possible pairing, this is the classical " Assignment Problem " , for(More)
—This paper uses an ant colony meta-heuristic optimization method to solve the redundancy allocation problem (RAP). The RAP is a well known NP-hard problem which has been the subject of much prior work, generally in a restricted form where each subsystem must consist of identical components in parallel to make computations tractable. Meta-heuristic methods(More)
The paper shows that the use of a memetic algorithm (MA), a genetic algorithm (GA) combined with local search, synergistically combined with Lagrangian relaxation is effective and efficient for solving large unit commitment problems in electric power systems. It is shown that standard implementations of GA or MA are not competitive with the traditional(More)
When designing computer or communications network topologies, a common reliability measure is all-terminal reliability, the probability that all nodes (computers or terminals) can communicate with all others. Exact calculation of all-terminal reliability is an NP-hard problem, precluding its use during optimal network topology design, where this calculation(More)