Fuzzy Simheuristics for Optimizing Transportation Systems: Dealing with Stochastic and Fuzzy Uncertainty

In the context of logistics and transportation, this paper discusses how simheuristics can be extended by adding a fuzzy layer that allows us to deal with complex optimization problems both stochastic uncertainty. This hybrid approach combines simulation, metaheuristics, logic generate near-optimal solutions large scale NP-hard typically arise in many transportation activities, including vehicle routing problem, arc or team orienteering problem. The methodology model different components–such as travel times, service customers’ demands–as deterministic, stochastic, fuzzy. A series computational experiments contribute validate our approach, which also other areas such manufacturing production, smart cities, telecommunication networks, etc.