A Hyrid Genetic Algorithm Approach for Solving Partner Constrained Lane Covering Problems

Year 2020, Volume: 22 Issue: 65, 401 - 416, 15.05.2020

Gültekin Kuyzu

https://doi.org/10.21205/deufmd.2020226509

Abstract

Partner
Constrained Lane Covering Problems (PCLCPs) are NP-Hard arc routing problems
arising in collaborative truckload transportation procurement networks. The
objective in these problems is to cover a set of full truckload shipment lanes
of multiple shippers using cyles, each of which may include lanes from
different shippers and empty truck movements, with minimum total cost such that
each shipper does not share cycles with more than a prespecified number of partners.
This paper presents a hybrid genetic algorithm (HGA) approach that combines
genetic algorithm, local search and large neighborhood search approaches for
solving PCLCPs.  This approach is the
first meta-heuristic that has been proposed for solving NP-Hard LCPs. The
proposed MGA has been tested on instances that were previously used in the
literature. It has improved the previous best known solutions of a significant
portion of the large scale instances that were tested. 

Keywords

lane covering problem, arc routing, hybrid genetic algorithm

Ortak Kısıtlı Rota Kapsama Problemlerinin Çözümü İçin Melez Genetik Algoritma Yaklaşımı

Abstract

Ortak Kısıtlı Rota Kapsama
Problemleri (OKRKP’ler) tam kamyon yükü hizmeti satın alma işbirliği ağlarında ortaya
çıkan NP-Zor ayrıt rotalama problemleridirler. Bu problemlerde amaç, işbirliği
yapan birden fazla gönderici firmanın tam kamyon yükü gönderi rotalarını,
birden fazla gönderici firmadan gönderi rotası ve boş kamyon hareketleri içerebilecek
ve göndericilerin çevrim paylaşmak istediği azami ortak sayılarını aşmadan
kapsayan en kısa toplam uzunluklu yönlü çevrimler kümesini bulmaktır. Bu
makale, OKRKP’lerin çözümü için geliştirilen; genetik algoritma, yerel arama ve
geniş komşuluk arama yaklaşımlarının birleşiminden oluşan bir melez genetik
algoritma (MGA) yaklaşımını sunmaktadır. Bu yaklaşım, NP-Zor RKP’lerin çözümü
için önerilen ilk meta-sezgisel çözüm yaklaşımıdır.  Önerilen MGA, daha önce literatürdeki
çalışmalarda kullanılan problem örnekleri üzerinde denenmiştir. Deneylerde
kullanılan büyük ölçekli problem örneklerinin önemli bir kısmında bilinen en
iyi çözümlerden daha iyi çözümler elde edilmiştir. 

Keywords

rota kapsama problemi, ayrıt rotalama, melez genetik algoritma

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