
In the last decades the Vehicle Routing Problem (VRP) and its ramifications, including the Capacitated Vehicle Routing Problem (CVRP), have attracted the attention of researchers mainly because their presence in many practical situations. Due to the difficulties encountered in their solutions, such problems are usually solved by means of heuristic and metaheuristics algorithms, among which is the Genetic Algorithm (GA). The solution of CVRP using GA requires a solution encoding step, which demands a special care to avoid high computational cost and to ensure population diversity that is essential for the convergence of GA to global optimal or sub-optimal solutions. In this work, we investigated a new binary encoding scheme employed by GA for solving the CVRP. Conducted experiments demonstrated that the proposed binary encoding is able to provide good solutions and is suitable for practical applications that require low computational cost.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
