A fast and effective MIP-based heuristic for a selective and periodic inventory routing problem in reverse logistics

We consider an NP-hard selective and periodic inventory routing problem (SPIRP) in a waste vegetable oil collection environment. This SPIRP arises the context of reverse logistics where biodiesel company has daily requirements to be used as raw material its production process. These can fulfilled by using available inventory, collecting or purchasing virgin oil. The consists determining period (cyclic) planning for such that total collection, costs are minimized, while meeting company’s all operational constraints. propose MIP-based heuristic which solves relaxed model without routing, constructs routes taking into account relaxation’s solution then improves these solving capacitated vehicle associated each period. Following this approach, posteriori performance guarantee is ensured, approach provides both lower bound feasible solution. performed computational experiments show very fast effective it able encounter near optimal solutions with low gaps within seconds, improving several best known results just fraction time spent state-of-the-art heuristic. A remarkable fact proposed over large instances literature.