A Computational Study of Genetic Crossover Operators for Multi-Objective Vehicle Routing Problem with Soft Time Windows

The article describes an investigation of the effectiveness of genetic algorithms for multi-objective combinatorial optimization (MOCO) by presenting an application for the vehicle routing problem with soft time windows. The work is motivated by the question, if and how the problem structure influences the effectiveness of different configurations of the genetic algorithm. Computational results are presented for different classes of vehicle routing problems, varying in their coverage with time windows, time window size, distribution and number of customers. The results are compared with a simple, but effective local search approach for multi-objective combinatorial optimization problems

PENENTUAN RUTE PENGANGKUTAN SAMPAH DENGAN MENGGUNAKAN METODE VEHICLE ROUTING PROBLEM (VRP) TIME WINDOWS UNTUK WILAYAH BANDUNG UTARA

Peningkatan jumlah sampah di kota Bandung ditunjang oleh sarana dan prasarana pengolahan sampah yang mendukung supaya tidak terjadi penumpukan sampah. Proses pengumpulan sampah merupakan kontribusi terbesar dalam biaya pengolahan sampah. Rute pengumpulan sampah dapat dibuat dengan memperhatikan keterbatasan yang ada, seperti : jumlah kendaraan, jumlah TPS, waktu angkut dan sistem pengangkutan sampah. Dengan keadaan kurangnya sistem pengangkutan sampah yang optimal khususnya pada Perusahaan Daerah Kebersihan Kota Bandung Wilayah Utara maka dilakukan kembali penelitian yang bertujuan untuk mendapatkan rute alternative pengangkutan sampah dengan mempertimakan biaya operasional. Kondisi pengumpulan sampah dapat dianalogikan dengan model Vehicle Routing Problem dengan menambahkan Time Windows setelah rute alternative di dapatkan. Vehicle Routing Problem with Time Windows (VRPTW) menyelesaikan permasalahan dengan dengan meminimalkan biaya untuk jarak tempuh dan jumlah kendaraan yang digunakan. Pengangkutan sampah ini mempertimbangkan waktu operasional pelayanannya. Dalam penentuan rute pengangkutan sampah wilayah Bandung Utara menggunakan metode savings dan clustering. Rute yang dapat dihasilkan menggunakan Vehicle Routing Problem with Time Windows berhasil menghemat jarak kurang lebih sejauh 37,9 Km, yaitu 38% dari jarak sebelumnya, menghemat waktu tempuh yang sebelumnya adalah kurang lebih 32 jam menjadi 27 jam yaitu dengan penghematan sebesar 5%. Vehicle Routing Problem with Time Windows juga berpengaruh terhadap biaya yang di gunakan untuk operasional. Biaya penghematan yaitu sebesar kurang lebih Rp. 6.065.800-, dan jika di persenkan penghematan sebesar 45%. Kata kunci : Pengangkutan sampah, Vehicle Routing Problem with Time Windows, Savings, Clusterin

Reachability cuts for the vehicle routing problem with time windows

This paper introduces a class of cuts, called reachability cuts, for the Vehicle Routing Problem with Time Windows (VRPTW). Reachability cuts are closely related to cuts derived from precedence constraints in the Asymmetric Traveling Salesman Problem with Time Windows and to k-path cuts for the VRPTW. In particular, any reachability cut dominates one or more k-path cuts. The paper presents separation procedures for reachability cuts and reports computational experiments on well-known VRPTW instances. The computational results suggest that reachability cuts can be highly useful as cutting planes for certain VRPTW instances.Routing; time windows; precedence constraints

Fast Ejection Chain Algorithms for Vehicle Routing with Time Windows

This paper introduces new ejection chain strategies to effectively target vehicle routing problems with time window constraints (VRPTW). Ejection chain procedures are based on the idea of compound moves that allow a variable number of solution components to be modified within any single iteration of a local search algorithm. The yardstick behind such procedures is the underlying reference structure, which is the structure that is used to coordinate the moves that are available for the local search algorithm. The main contribution of the paper is a new reference structure that is particularly suited in order to handle the asymmetric aspects in a VRPTW. The new reference structure is a generalization of the doubly rooted reference structure introduced by Glover, resulting in a new, powerful neighborhood for the VRPTW. We use tabu search for the generation of the ejection chains. On a higher algorithmic level, we study the effect of different meta heuristics to steer the tabu chain ejection process. Computational results confirm that our approach leads to very fast algorithms that can compete with the current state of the art algorithms for the VRPTW.operations research and management science;