Bi-objective inventory routing problem with backhauls under transportation risks: two meta-heuristics

ABSTRACT

This paper considers a multi-period and product inventory-routing problem. This model involves two levels, namely, a distributor and several retailers. This problem is modeled with the aim of minimizing bi-objectives, namely, the total cost of the system (including start-up, distribution, and maintenance costs) and risk-based transportation. Products are delivered to retailers by some heterogeneous vehicles with specific capacities through a direct delivery strategy, and inventory shortage is assumed to be impermissible. To validate this new bi-objective model, the ε-constraint method is used to solve problems. Because problems without distribution planning are very complex to solve optimally, the problem considered in this paper is also Non-deterministic Polynomial (NP-hard). Therefore, a nondominated sorting genetic algorithm (NSGA-II) and a multi-objective imperialist competitive algorithm (MOICA) are used and developed to solve a number of test problems. Furthermore, the computational results are compared and the performance of the foregoing algorithms is analyzed.

KEYWORDS:

• Inventory-routing problem
• bi-objective model
• ε-constraint method
• multi-objective meta-heuristic algorithms

Disclosure statement

No potential conflict of interest was reported by the authors.