A simheuristic algorithm for the capacitated location routing problem with stochastic demands

The capacitated location routing problem (CLRP) integrates a facility location problem with a multi-depot vehicle routing problem. We consider the CLRP with stochastic demands, whose specific values are only revealed upon reaching each customer. The main goal is to minimise the expected costs of: (i) opening facilities, (ii) using a fleet of vehicles, (iii) executing a routing plan, and (iv) applying corrective actions. The latter are required whenever a route failure occurs due to unexpected high demands. We propose a simheuristic algorithm hybridizing simulation with an iterated local search metaheuristic, aimed at: (i) proposing a safety-stock policy to diminish the likelihood of route failure; and, (ii) estimating the expected cost and the reliability of each elite solution. We assess our approach on classical CLRP benchmarks, which are later extended to consider demand uncertainty. Finally, we also discuss the effects of the safety-stock policy on costs and reliability.

Automated summary

The CLRP integrates facility location problem with a multi-depot vehicle routing problem, considering stochastic demands only revealed upon reaching each customer. A simheuristic algorithm is proposed to propose a safety-stick policy to reduce route failure likelihood and estimate the cost and reliability of each elite solution.