The importance of routing and shortest path problems in the study of transportation networks is well-known. For instance, these are used to describe user behavior, to find equilibrium states of large-scale networks, and to evaluate the impact of network improvements and broader transportation policies. Thus, the development of efficient, behaviorally realistic algorithms is of paramount interes...

In existing metaheuristics for solving the capacitated arc routing problem, traversal local search operators are often used to explore neighbors of the current solutions. This mechanism is beneficial for finding high-quality solutions; however, it entails a large number of function evaluations, causing high computational complexity. Hence, there is a need to further enhance the efficiency of su...

In this chapter, a new dynamic capacitated arc routing problem (CARP) is defined and investigated. Compared with the static CARP and other dynamic CARP investigated by the existing researches, the new dynamic CARP is more general and closer to reality, and thus is more worthwhile to be solved. Due to the stochastic factors included in the dynamic CARP, the objective is not to obtain the optimal...

In this paper, we present a new Ant Colony System (ACS) approach for the Periodic Capacitated Arc Routing Problem (PCARP) on a mixed network. In the CARP problem the objective is to find routes starting from the depot such that each required arc/edge (called task) is serviced, capacity constraints are satisfied and total travel cost is minimized. The PCARP extends the classical CARP problem to ...

The Capacitated Arc Routing Problem (CARP) is a combinatorial optimization problem, which requires the identification of such route plans on given graph to number vehicles that generates least total cost. Dynamic CARP (DCARP) variation considers dynamic changes in problem. Artificial Bee Colony (ABC) algorithm an evolutionary was proven be able provide better performance than many other algorit...