A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem

Abstract

The heterogeneous fleet vehicle routing problem is investigated using some adaptations of the variable neighborhood search (VNS). The initial solution is obtained by Dijkstra's algorithm based on a cost network constructed by the sweep algorithm and the 2-opt. Our VNS algorithm uses several neighborhoods which are adapted for this problem. In addition, a number of local search methods together with a diversification procedure are used. Two VNS variants, which differ in the order the diversification and Dijkstra's algorithm are used, are implemented. Both variants appear to be competitive and produce new best results when tested on the data sets from the literature. We also constructed larger data sets for which benchmarking results are provided for future comparison.

Improving delivery routes using combined heuristic and optimization in a consumer goods distribution company

“…While reduced complexity allows more in-depth study of the problem on hand, it deviates from reality in industrial applications. In contrast to the number of general VRP articles cited in [9], only 22 articles related to HVRP were published between 1984 and 2007 [11]. In this particular area where analytical approach is hardly efficient, metaheuristics spur as sensible substitute in dealing with complex VRP problems.…”

“…In this particular area where analytical approach is hardly efficient, metaheuristics spur as sensible substitute in dealing with complex VRP problems. A few successful examples worth mentioning are record-to-record [12], scatter search [13], genetic algorithm [14], variable neighborhood search [11], multi-start adaptive memory programming [15], iterated local search [16], and tabu search [17].…”

Comparative analysis of granular neighborhoods in a Tabu Search for the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP)

“…Additionally, hybrid algorithms to solve the HFVR have been proposed by [4,[17][18][19][20][21][22]: [17] proposed an algorithm of iterated local search (ILS), combined with a search of variable neighborhoods decline (VND) and a randomly neighborhood ordering (RVND); [18], an algorithm based on a variable neighborhood search (VNS) with several neighborhoods in the phase of local search; [19], an algorithm based on the development of a series of classical heuristics for the traditional VRP, followed by a local search (SDLS) and a TS; [20], an algorithm based on a procedure of adaptive memory with multi-start (multi-start AMP) and a modification of the traditional TS; [21], a method called threshold of acceptance (Threshold Accepting Approach), which adapts the procedure of simulated annealing (SA); and finally, [22] proposed a combination of the algorithm record-to-record with the method of the threshold of acceptance to solve the two variants of the HFVRP.…”

A two-phase iterative procedure for the production, inventory and distribution routing problem

“…Note that in the first iteration, since the inventory at the customer sites is all equal to zero and the production quantity and inventory at the production facility are not considered, we use the three neighborhood structures (used in VRP) defined in Imran et al [15] with in the shaking step. These include the 1-1 lambda interchange as , the 2-0 shift as and the 2-1 interchange as .…”

“…The local search consists of six refinement procedures adopted from [15]. The order of the refinement procedure is as follows: the 1-insertion inter-route as , the 2-opt inter-route as , the 2-opt intra route as , the swap intra route as , 1-insertion intra-route as and at last, the 2-insertion intra-route as .…”