A population based simulated annealing algorithm for capacitated vehicle routing problem

İlhan, İlhan

doi:10.3906/elk-1902-122

Cited by 17 publications

(9 citation statements)

References 22 publications

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“…As in the case of the TSP, the CVRP is a combinatorial problem of NP-hard complexity which cannot be solved within a reasonable polynomial time [12]. Due to this, the CVRP has been addressed by different meta-heuristics such as Tabu -Search (TS) [13,14], GA [15], SA [16,17], and Particle Swarm Optimization (PSO) [18]. For this case, the GA presented in Figure 2 was modified to solve the CVRP.…”

Section: Capacitated Vehicle Routing Problemmentioning

confidence: 99%

Search Algorithms on Logistic and Manufacturing Problems

Bonilla-Enríquez¹,

Caballero‐Morales²

2023

Search Algorithm - Essence of Optimization

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The supply chain comprehensively considers problems with different levels of complexity. Nowadays, design of distribution networks and production scheduling are some of the most complex problems in logistics. It is widely known that large problems cannot be solved through exact methods. Also, specific optimization software is frequently needed. To overcome this situation, the development and application of search algorithms have been proposed to obtain approximate solutions to large problems within reasonable time. In this context, the present chapter describes the development of Genetic Algorithms (an evolutionary search algorithm) for vehicle routing, product selection, and production scheduling problems within the supply chain. These algorithms were evaluated by using well-known test instances. The advances of this work provide the general discussions associated to designing these search algorithms for logistics problems.

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Section: Capacitated Vehicle Routing Problemmentioning

confidence: 99%

Search Algorithms on Logistic and Manufacturing Problems

Bonilla-Enríquez¹,

Caballero‐Morales²

2023

Search Algorithm - Essence of Optimization

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“…The PSO algorithm has a fast convergence rate, but the results are random. Ilhan [ 10 ] studied CVRP and proposed a new population-based simulated annealing algorithm, which used three different route development operators, namely, exchange, inserting, and reversion regression operators. Most studies are based on the fixed amount of garbage.…”

Section: Literature Reviewmentioning

confidence: 99%

A Cross-Regional Scheduling Strategy of Waste Collection and Transportation Based on an Improved Hierarchical Agglomerative Clustering Algorithm

Wei

Liang

Tang

2022

Computational Intelligence and Neuroscience

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The disposal of municipal solid waste (MSW) is based on the divide-regional operation model at present, which brings management convenience. However, due to the constraints of the division between the operating regions, there are problems such as inflexible vehicle scheduling and low efficiency. Changing this mode will put pressure on management. It is necessary to break the constraint of the region and form a fully automatic operating scheme without too much manual management. First, the initial clusters are formed by considering the distance in the initial allocation module. Secondly, through the type labeling and reallocation module, the single big data set is transformed into multiple small data sets by considering the allocated amount of garbage and the carrying capacity of garbage vehicles. Then, this work proposes the improved hierarchical agglomerative clustering (IHAC) algorithm and the garbage collecting path planning (GCPP) algorithm to realize the intelligent allocation of waste and scheduling route planning of garbage vehicles. Finally, through simulation by real example and comparative analysis, the advantages of the proposed scheme are discussed. The results show that the proposed scheme is more effective than the original scheme and other advanced methods, which can provide decision support for the scientific and intelligent collection and transportation of MSW.

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“…Bu neden ile BTA'nın performansı büyük ölçüde başlangıç değerine bağlıdır. Başlangıç değerinin kalitesi zayıfsa, sonuç yetersiz olur [27]. Bu sebeple, aramaya yeteri kadar yüksek bir sıcaklık değeri ile başlamak gereklidir [28].…”

Section: Benzetimli Tavlama Algoritmasıunclassified

Benzetimli Tavlama Algoritması İle Eksik Veri Tamamlama

Metin¹

2021

Fırat Üniversitesi Mühendislik Bilimleri Dergisi

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Öz: İstatiksel birçok yöntem eksik değerlere sahip veri setleri üzerinde çalışma kapasitesine sahip değildir. Bu nedenle, girdi olarak yalnızca tam veriyi kabul eden modellerin tahmin performansı önemli ölçüde düşmektedir. Eksik verilerin tamamlanması bunun için veri analizlerinde önemli bir yere sahiptir. Bu çalışmada kullanılan veri seti üzerinde eksik olan verilerin tamamlanma probleminin çözümünde sezgisel optimizasyon yöntemi olan Benzetimli Tavlama Algoritması(BTA) kullanılmıştır. Modern sezgisel teknikler, bir problem çözümünde, kendi yerel arama sistemleri ile en iyi sonuca ulaşmayı amaçlamaktadırlar. BTA performansını etkileyen en önemli değer başlangıç sıcaklık değeri (T0) olduğundan üç farklı sıcaklık değeri ile sonuçlar alınmıştır. To=100.000 değeri için %68, To=10.000 için %51 ve To=1.000 için %46'lik bir başarı elde edilmiştir.

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A population based simulated annealing algorithm for capacitated vehicle routing problem

Cited by 17 publications

References 22 publications

Search Algorithms on Logistic and Manufacturing Problems

Search Algorithms on Logistic and Manufacturing Problems

A Cross-Regional Scheduling Strategy of Waste Collection and Transportation Based on an Improved Hierarchical Agglomerative Clustering Algorithm

Benzetimli Tavlama Algoritması İle Eksik Veri Tamamlama

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