Benchmark dataset for the Asymmetric and Clustered Vehicle Routing Problem with Simultaneous Pickup and Deliveries, Variable Costs and Forbidden Paths

In this paper, the benchmark dataset for the Asymmetric and Clustered Vehicle Routing Problem with Simultaneous Pickup and Deliveries, Variable Costs and Forbidden Paths is presented (AC-VRP-SPDVCFP). This problem is a specific multi-attribute variant of the well-known Vehicle Routing Problem, and it has been originally built for modelling and solving a real-world newspaper distribution problem with recycling policies. The whole benchmark is composed by 15 instances comprised by 50–100 nodes. For the design of this dataset, real geographical positions have been used, located in the province of Bizkaia, Spain. A deep description of the benchmark is provided in this paper, aiming at extending the details and experimentation given in the paper A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy (Osaba et al.) [1]. The dataset is publicly available for its use and modification.Eneko Osaba would like to thank the Basque Government for its funding support through the EMAITEK and ELKARTEK

A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy

A real-world newspaper distribution problem with recycling policy is tackled in this work. In order to meet all the complex restrictions contained in such a problem, it has been modeled as a rich vehicle routing problem, which can be more specifically considered as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP). This is the first study of such a problem in the literature. For this reason, a benchmark composed by 15 instances has been also proposed. In the design of this benchmark, real geographical positions have been used, located in the province of Bizkaia, Spain. For the proper treatment of this AC-VRP-SPDVCFP, a discrete firefly algorithm (DFA) has been developed. This application is the first application of the firefly algorithm to any rich vehicle routing problem. To prove that the proposed DFA is a promising technique, its performance has been compared with two other well-known techniques: an evolutionary algorithm and an evolutionary simulated annealing. Our results have shown that the DFA has outperformed these two classic meta-heuristics

A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy

A real-world newspaper distribution problem with recycling policy is tackled in this work. In order to meet all the complex restrictions contained in such a problem, it has been modeled as a rich vehicle routing problem, which can be more specifically considered as an asymmetric and clustered vehicle routing problem with simultaneous pickup and deliveries, variable costs and forbidden paths (AC-VRP-SPDVCFP). This is the first study of such a problem in the literature. For this reason, a benchmark composed by 15 instances has been also proposed. In the design of this benchmark, real geographical positions have been used, located in the province of Bizkaia, Spain. For the proper treatment of this AC-VRP-SPDVCFP, a discrete firefly algorithm (DFA) has been developed. This application is the first application of the firefly algorithm to any rich vehicle routing problem. To prove that the proposed DFA is a promising technique, its performance has been compared with two other well-known techniques: an evolutionary algorithm and an evolutionary simulated annealing. Our results have shown that the DFA has outperformed these two classic meta-heuristics

Optimized Model Simulation of a Capacitated Vehicle Routing problem based on Firefly Algorithm

This paper presents an optimized solution to a capacitated vehicle routing (CVRP) model using firefly algorithm (FFA). The main objective of a CVRP is to obtain the minimum possible total travelled distance across a search space. The conventional model is a formal description involving mathematical equations formulated to simplify a more complex structure of logistic problems. These logistic problems are generalized as the vehicle routing problem (VRP). When the capacity of the vehicle is considered, the resulting formulation is termed the capacitated vehicle routing problem (CVRP). In a practical scenario, the complexity of CVRP increases when the number of pickup or drop-off points increase making it difficult to solve using exact methods. Thus, this paper employed the intelligent behavior of FFA for solving the CVRP model. Two instances of solid waste management and supply chain problems is used to evaluate the performance of the FFA approach. In comparison with particle swarm optimization and few other ascribed metaheuristic techniques for CVRP, results showed that this approach is very efficient in solving a CVRP model

Design and Implementation of a Combinatorial Optimization Multi-population Meta-heuristic for Solving Vehicle Routing Problems

This paper aims to give a presentation of the PhD defended by Eneko Osaba on November 16th, 2015, at the University of Deusto. The thesis can be placed in the field of artificial intelligence. Specifically, it is related with multi- population meta-heuristics for solving vehicle routing problems. The dissertation was held in the main auditorium of the University, in a publicly open presentation. After the presentation, Eneko was awarded with the highest grade (cum laude). Additionally, Eneko obtained the PhD obtaining award granted by the Basque Government through

Investigating Modeling and Solving a Hybrid Problem Considering the Simultaneous Loading and Delivery of the Vehicle and the Locating of Facilities for Storing and Recycling in a Three-Level Green Supply Chain

Today, In this research, we intend to study the modeling and solving a hybrid problem considering the simultaneous loading and delivery of the vehicle and the locating of facilities for storing and recycling in a three-level green supply chain. This issue is known as 3-level mapping routing issue in the subject literature. With the goal of presenting a mathematical model for the vehicle routing problem and locating the storage facilities and recycling facilities in a green supply chain network, an efficient algorithm is developed to optimize the problem and compare the performance of the algorithm with known algorithms such as genetics. Also one of the other purposes is to find a combination of truck and facility paths so that results in minimum transfer costs in a direct and reverse manner. By reviewing the recent articles and discovering the existing research gap, we will develop a problem model with a specific application, and eventually we will overwrite the problem in the framework of the language of the meta-innovative algorithms to solve the problem by the meta-innovative method. To compare the efficiency of the meta-innovative algorithm developed in this research and its validation, we will compare the results with a precise method using GAMS software for small issues. Also, one of the genetic algorithms can be used to test the performance of the algorithm. This research is considered within the framework of applied research regarding the orientation, because using the results of this study, some suggestions can be made to solve specific problems in the organization. In addition, this research is a descriptive method in which mathematical and modeling tools are used. Keywords: Logistic Network, Green Supply Chain, Locating and Routing Problem, Combined or Hybrid Meta-Innovative Algorith

PENYELESAIAN VRPSDP MENGGUNAKAN FIREFLY ALGORITHM (STUDI KASUS DISTRIBUSI AQUA GALON)

Penyelesaian masalah distribusi Aqua galon termasuk dalam pengaplikasian kompleks Vehicle Routing Problem with Simultaneos Delivery and Pickup (VRPSDP). VRPSDP bisa diselesaikan dengan metode eksak, heuristik atau meta-heuristik. Firefly Algorithm merupakan salah satu algoritma meta-heuristik yang terinspirasi oleh perilaku dan cara komunikasi serangga kunang-kunang dengan melalui beberapa tahapan, yaitu intensitas cahaya, tingkat daya tarik, pergerakan, dan mutasi pembalikan. Metode Firefly Algorithm dalam penelitian ini digunakan untuk mencari solusi optimal dalam menyelesaikan permasalahan tersebut. Hasil penelitian menunjukkan bahwa Firefly Algorithm dapat memberikan solusi yang mana mendekati optimal dalam waktu yang relatif lebih singkat dibandingkan dengan metode eksak

Good practice proposal for the implementation, presentation, and comparison of metaheuristics for solving routing problems

Researchers who investigate in any area related to computational algorithms (both dening new algorithms or improving existing ones) usually nd large diculties to test their work. Comparisons among dierent researches in this eld are often a hard task, due to the ambiguity or lack of detail in the presentation of the work and its results. On many occasions, the replication of the work conducted by other researchers is required, which leads to a waste of time and a delay in the research advances. The authors of this study propose a procedure to introduce new techniques and their results in the eld of routing problems. In this paper this procedure is detailed, and a set of good practices to follow are deeply described. It is noteworthy that this procedure can be applied to any combinatorial optimization problem. Anyway, the literature of this study is focused on routing problems. This eld has been chosen because of its importance in real world, and its relevance in the actual literature