• a bi-criteria network model for a flexible manufacturing system in which both time and cost serve as performance criteria • to identify an optimal path in a bi-criteria network in which the path cost is evaluated in fractional form • to prevent bottlenecks and increase system reliability while minimizing waiting time, idle time, and transportation costs An Automated Guided Vehicle (AGV) is a type of material-handling equipment that travels along a predefined guide-path network. One of the key challenges in AGV routing is determining an optimal path in a multi-criteria network such that a path-dependent cost function is minimized. Many real-world decision-making problems can be formulated using complex networks with conflicting criteria. A fundamental problem in such systems is the Multi-Criteria Shortest Path Problem (MSPP), where each arc is associated with at least two attributes. MSPP has numerous applications across various domains. In this study, we investigate a bi-criteria network model for a flexible manufacturing system in which both time and cost serve as performance criteria due to the flexible nature of the material-handling environment. The objective is to identify an optimal path in a bi-criteria network in which the path cost is evaluated in fractional form. The proposed model allows system designers to prevent bottlenecks and increase system reliability while minimizing waiting time, idle time, and transportation costs. Computational results show that the optimal path obtained yields the shortest route with minimal cost and maximum reliability.
Hamed Fazlollahtabar (Sun,) studied this question.