Towards Novel Meta-heuristic Algorithms for Dynamic Capacitated Arc Routing Problems

Abstract

The capacitated arc routing problem (CARP) is a challenging combinatorial optimisation problem abstracted from typical real-world applications, like waste collection and mail delivery. However, few studies considered dynamic changes during the vehicles' service, which can make the original schedule infeasible or obsolete. The few existing studies are limited by dynamic scenarios that can suffer single types of dynamic events, and by algorithms that rely on special operators or representations, being unable to benefit from the wealth of contributions provided by the static CARP literature. Here, we provide the first mathematical formulation for dynamic CARP (DCARP) and design a simulation system to execute the CARP solutions and generate DCARP instances with several common dynamic events. We then propose a novel framework able to generalise all existing static CARP optimisation algorithms so that they can cope with DCARP instances. The framework has the option to enhance optimisation performance for DCARP instances based on a restart strategy that makes no use of past history, and a sequence transfer strategy that benefits from past optimisation experience. Empirical studies are conducted on a wide range of DCARP instances. The results highlight the need for tackling dynamic changes and show that the proposed framework significantly improves over existing algorithms.

A Novel Generalized Metaheuristic Framework for Dynamic Capacitated Arc Routing Problems

“…For DCARP, the calculation of cost and capacity violation of the routes corresponding to the outside vehicles are required to be specifically considered due to the fact that outside vehicles have different locations and remaining capacities. It is more complicated to use an ordered list of tasks as the solution representation during the optimisation because the Ulusoy's split [3] is not suitable anymore and specific split schemes [25] are required. Even though a new split scheme was proposed in our previous work [25], its high computational complexity limits its performance.…”

“…It is more complicated to use an ordered list of tasks as the solution representation during the optimisation because the Ulusoy's split [3] is not suitable anymore and specific split schemes [25] are required. Even though a new split scheme was proposed in our previous work [25], its high computational complexity limits its performance. Therefore, the existing algorithm for static CARP [16] is adapted to solve DCARP instance with some modification, such as the existing work in [16].…”

“…Overall, we can conclude that VT-MASDC performs much better than the original MASDC. MASDC uses a distance-based split scheme (DSS) to evaluate DCARP solution's fitness because the split scheme designed for static CARP is not suitable for DCARP [25]. The DSS operator randomly splits the sequence of tasks to an executable CARP solution with explicit routes, and the random splitting process is repeated three times to obtain a better schedule.…”

“…Wasin et al [23] considered new tasks in DCARP. A robot path planning problem [24] and our previous work [25] focused on the split scheme in DCARP. Split schemes convert an ordered task sequence into an executable solution of multiple explicit routes.…”

Genetic Programming With Niching for Uncertain Capacitated Arc Routing Problem

“…Uncertain CARP (UCARP) [5]- [7] was proposed to better reflect the reality. A variety of uncertainties, such as the stochastic task presence and demand, stochastic edge deadheading cost and stochastic travel time, have been considered [6].…”