Solve scheduling problems with a fuzzy approach

Implementation of Shape – Based Matching Vision System in Flexible Manufacturing System

“…Whether the researchers are trying to improve an existing FMS, simulating or designing a new FMS, the main objective is to find the shortest lead time and higher utilization of facilities. There are a lot of different approach that was studied, scheduling algorithm like taboo search [2], heuristic approach [3], filtered-beam-search [4], branch and bound [5] by using different control theory such as fuzzy logic [6], [7], neural network [4], genetic algorithm [8], [9] and many more. The common point that most of these article share are most likely the set of dispatching rules, including Earliest Due Date, Shortest Processing Time, First Come First Serve, Most Work Remaining, Least Work Remaining, Longest Operation Processing Time and many more.…”

Partial Adjustable Autonomy in Multi-Agent Environment and Its Application to Military Logistics

“…[6] extended this problem to Distributed Constraint Optimization Problem as well and proposed the ADOPT algorithm which guaranteed a user-defined optimality. [8] also provide an algorithm (Ap-tOPT) to solve distributed Constraint Optimization Problem, which experimentally performs better than ADOPT.…”

“…The five-stage fuzzy process listed below has been extensively reported [4] [8]. In the following, we define the function L i (e 1 , e 2 , ..., e m ) as consisting of:…”