Variable Very Large Neighborhood Algorithms for Truck Sequencing at Transshipment Terminals

Abstract

This paper considers a scheduling problem motivated by transshipment terminals. Trucks delivering or picking up items at the terminal have to be sequenced. Here, inventory constraints must be considered, that is the current inventory level implied by initial inventory level, total amount if pick up, and total amount delivery must not be negative and must not exceed the inventory’s capacity. We consider objective function common in scheduling theory, namely minimization of maximum lateness, total weighted completion time, total weighted tardiness, or weighted number of tardy trucks. We employ a local search strategy using a representation scheme where each individual corresponds to at least one and potentially an exponential number of feasible solutions. We propose several neighborhoods embedded in a variable neighborhood search algorithm. We provide polynomial time algorithms to derive the optimal corresponding solution from an individual and show efficiency of the neighborhood search algorithm by means of a computational study.