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2016•Jurnal TeknologiOpen access

A VARIABLE NEIGHBORHOOD SEARCH FOR THE HETEROGENEOUS FIXED FLEET VEHICLE ROUTING PROBLEM

Arif Imran, Martino Luis, Liane Okdinawati

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Abstract

The heterogeneous fixed fleet vehicle routing problem (HFFVRP) is investigated using the variable neighborhood search (VNS). The initial solution is generated using the Sweep algorithm and the 2-opt procedure and then the customers are allocated to the smallest vehicle first by considering vehicle occupancy level. The proposed VNS algorithm uses several neighborhoods and a number of local search methods which are adapted for this problem. The local searches are implemented within a multi-level framework. The performance of the proposed algorithm is then tested using data set taken from literature and the experiments show competitive results with less computing time. Future research directions are also highlighted.

About this research paper

What this paper is about

The heterogeneous fixed fleet vehicle routing problem (HFFVRP) is investigated using the variable neighborhood search (VNS). The initial solution is generated using the Sweep algorithm and the 2-opt procedure and then the customers are allocated to the smallest vehicle first by considering vehicle occupancy level. The proposed VNS algorithm uses several neighborhoods and a number of local search methods which are adapted for this problem. The local searches are implemented within a multi-level framework. The performance of the proposed algorithm is then tested using data set taken from literature and the experiments show competitive results with less computing time. Future research directions are also highlighted.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

The heterogeneous fixed fleet vehicle routing problem (HFFVRP) is investigated using the variable neighborhood search (VNS). The initial solution is generated using the Sweep algorithm and the 2-opt procedure and then the customers are allocated to the smallest vehicle first by considering vehicle occupancy level. The proposed VNS algorithm uses several neighborhoods and a number of local search methods which are adapted for this problem. The local searches are implemented within a multi-level framework. The performance of the proposed algorithm is then tested using data set taken from literature and the experiments show competitive results with less computing time. Future research directions are also highlighted.

Key concepts: Vehicle routing problem, Variable neighborhood search, Variable (mathematics), Local search (optimization), Set (abstract data type), Computer science, Mathematical optimization, Routing (electronic design automation)

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