An Improved Simulated Annealing for the Capacitated Vehicle Routing Problem (Cvrp)

Mar'i, Farhanna; Mahmudy, Wayan Firdaus; Santoso, Purnomo Budi

doi:10.28961/kursor.v9i3.178

Cited by 7 publications

(8 citation statements)

References 14 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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“…In [17] improved K-nearest neighbour algorithm is used to solve capacitated VRP (CVRP). In [18] an improved simulated annealing for the CVRP is described. In [19], an Evolutive Tabu-Search approach is used for CVRP.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Data-Driven Approach to Solve Real-World Vehicle Routing Problems in Logistics

2020

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Transportation occupies one-third of the amount in the logistics costs, and accordingly transportation systems largely influence the performance of the logistics system. This work presents an adaptive data-driven innovative modular approach for solving the real-world Vehicle Routing Problems (VRP) in the field of logistics. The work consists of two basic units: (i) an innovative multi-step algorithm for successful and entirely feasible solving of the VRP problems in logistics, (ii) an adaptive approach for adjusting and setting up parameters and constants of the proposed algorithm. The proposed algorithm combines several data transformation approaches, heuristics and Tabu search. Moreover, as the performance of the algorithm depends on the set of control parameters and constants, a predictive model that adaptively adjusts these parameters and constants according to historical data is proposed. A comparison of the acquired results has been made using the Decision Support System with predictive models: Generalized Linear Models (GLM) and Support Vector Machine (SVM). The algorithm, along with the control parameters, which using the prediction method were acquired, was incorporated into a web-based enterprise system, which is in use in several big distribution companies in Bosnia and Herzegovina. The results of the proposed algorithm were compared with a set of benchmark instances and validated over real benchmark instances as well. The successful feasibility of the given routes, in a real environment, is also presented.Keywords Vehicle routing problem  Multi-step algorithm  Data-driven approach  Parameter setting problem  Real-world constraints in logistics

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“…Nowadays, numerous papers have developed various heuristic and metaheuristic methods to solve CVRP problems, such as particle swarm optimization (Ahmed & Sun 2018;Alinezhad et al, 2018;Iswari & Asih, 2018;Mauliddina et al, 2020;Ramadhani & Garside, 2021;Son & Tan, 2021). Simulated annealing algorithm also was proposed by Aurachman et al, 2021;Ilhan, 2020;Mari et al, 2018;Rabbouch et al, 2020;Redi et al, 2020. Besides, there are several studies about CVRP using genetic algorithm (Abdelatti et al, 2021;Azad & Hasin, 2019;Lima & Araújo, 2018;Mulloorakam & Nidhiry, 2019;Zhu, 2022).…”

Section: Introductionmentioning

confidence: 99%

Solving Capacitated Vehicle Routing Problem Using Football Game Algorithm

Alif¹,

Garside

Amallynda³

et al. 2022

JITI

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The Capacitated Vehicle Routing Problem (CVRP) plays an important role in the logistics transportation sector. Determining the proper route will reduce the company's operational costs. In CVRP, a number of vehicles have a capacity limit that can serve all customers. This research completes a real case study on a bottled drinking water company where the company still uses the subjective method of the driver to determine the transportation route. Based on the conditions in the company, the selection of the best route will consider vehicle capacity and demand to determine the shortest route. The execution of this case study uses the Football Game Algorithm (FGA) which was first initiated by Fadakar Ebrahimi which proved promising and had the strongest performance in all cases. FGA is expected to be able to determine the shortest distribution route from the existing cases to reduce the distribution costs incurred. This study takes data from 4 days of delivery that served 78 customers. The average daily transportation cost savings result is 42%. This amount indicates that the FGA algorithm is effective for completing a real case study in CVRP.

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An Improved Simulated Annealing for the Capacitated Vehicle Routing Problem (Cvrp)

Cited by 7 publications

References 14 publications

Search Algorithms on Logistic and Manufacturing Problems

Search Algorithms on Logistic and Manufacturing Problems

An Adaptive Data-Driven Approach to Solve Real-World Vehicle Routing Problems in Logistics

Solving Capacitated Vehicle Routing Problem Using Football Game Algorithm

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