An improved differential evolution algorithm for vehicle routing problem with simultaneous pickups and deliveries and time windows

Lai, Mingyong; Cao, Erbao

doi:10.1016/j.engappai.2009.09.001

Cited by 123 publications

(52 citation statements)

References 18 publications

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“…Bila vektor merupakan bilangan real, maka harus diubah menjadi bilangan integer dengan metode integer order criterion (Mingyong dan Erbao [10] Penyelesaian VRP secara manual menggunakan sebuah set data berukuran kecil untuk meminimalkan jumlah iterasi yang harus dilakukan sesuai langkah-langkah algoritma yang diusulkan. Set data tersebut diambil dari penelitian yang dilakukan oleh Rera [11].…”

Section: Pembangkitan Vektor Mutanunclassified

Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem

Garside¹,

Sudaningtyas²

2014

jti

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Genetic Algorithm, Tabu Search, Simulated Annealing, and Ant Colony Optimization showed a good performance in solving vehicle routing problem. However, the generated solution of those algorithms was changeable regarding on the input parameter of each algorithm. CODEQ is a new, parameter free meta-heuristic algorithm that had been successfully used to solve constrained optimization problems, integer programming, and feed-forward neural network. The purpose of this research are improving CODEQ algorithm to solve vehicle routing problem and testing the performance of the improved algorithm. CODEQ algorithm is started with population initiation as initial solution, generated of mutant vector for each parent in every iteration, replacement of parent by mutant when fitness function value of mutant is better than parent's, generated of new vector for each iteration based on opposition value or chaos principle, replacement of worst solution by new vector when fitness function value of new vector is better, iteration ceasing when stooping criterion is achieved, and sub-tour determination based on vehicle capacity constraint. The result showed that the average deviation of the best-known and the best-test value is 6.35%. Therefore, CODEQ algorithm is good in solving vehicle routing problem.Keywords: Algorithm, meta-heuristic, vehicle routing problem, CODEQ. PendahuluanCombinatorial problem merupakan suatu permasalahan matematis untuk menyusun, mengelompokkan, mengurutkan, atau memilih sejumlah objek diskrit tertentu (Lawler [1]). Sampai saat ini, combinatorial problem masih menjadi salah satu bidang yang sering diteliti karena dengan semakin berkembangnya ilmu pengetahuan diharapkan akan ditemukan metode-metode maupun pendekatanpendekatan baru yang bisa menjadi sebuah cara penyelesaian terbaik untuk permasalahan ini.

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Section: Pembangkitan Vektor Mutanunclassified

Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem

Garside¹,

Sudaningtyas²

2014

jti

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“…El propósito es minimizar el costo de la distancia recorrida bajo cierto conjunto de restricciones. Las cuatro variantes de VRP más estudiadas son: VRP con Restricciones Capacitadas (CVRP), VRP con Ventanas de Tiempo (VRPTW), VRP con Backhauls (VRPB) y VRP con Recogidas y Entregas (VRPPD) (Cordeau et al, 2007;Mingyong y Erbao, 2010). Basado en estas variantes básicas, la investigación en VRP ha generado una amplia gama de problemas surgidos de situaciones particulares, especialmente en contextos urbanos (Kim et al, 2015).…”

Section: Introductionunclassified

Una Solución al Enrutamiento de Vehículos en Ciudades Montañosas Considerando Aspectos Ambientales y Económicos

2018

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_____________________________________________________________________________________________________________________________________ ResumenEste trabajo aborda un problema de enrutamiento de vehículos en ciudades de montaña, para determinar la más óptima. Actualmente el transporte verde se ha convertido en un tema de gran interés debido a su relación directa con el costo operativo y su impacto en el medio ambiente. Tradicionalmente se ha considerado que la ruta más corta minimiza tanto costos como emisiones. Sin embargo, la topografía del terreno en montañas es una particularidad que debe ser considerada con miras a lograr soluciones más acordes con la realidad. Para este estudio, se propone un modelo matemático multiobjetivo, el cual determina una ruta que logra un adecuado balance entre el costo del transporte y el impacto ambiental. El modelo se aplicó en un canal de distribución minorista de una ciudad andina de Colombia. Se concluyó que, en escenarios de montaña, la ruta más corta no es necesariamente la mejor, debido al impacto de la pendiente en el consumo de combustible y en las emisiones de CO2. Palabras clave: enrutamiento de vehículos; consumo de combustible; emisiones de CO2; pendiente de la carretera; multiobjetivo A Vehicle Routing Solution for Hilly Cities Considering Environmental and Economic Issues AbstractThis paper addresses a vehicle routing problem in mountainous cities with the objective of finding the optimum route. Currently, green transportation has become a topic of great interest due to its direct relation with operational costs and its impact on the environment. Traditionally, the shortest route has been considered to minimize both costs and emissions. However, topography in mountains is a particularity that must be considered in order to achieve more realistic solutions. For this study, a multi-objective mathematical model is proposed to determine a route that achieve a proper balance between transportation cost and environmental impact. The model was applied in a retail distribution channel of an Andean city in Colombia. It was concluded that in mountain scenarios, the shortest route is not necessarily the optimum, due to the impact of slope on fuel consumption and CO2 emissions.

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“…Together with the model, several assumptions have been identified to describe the model [12]. The assumptions are listed as follows: 1) There is a demand required by each and every customer in the network.…”

Section: Vrptw Modelmentioning

confidence: 99%

An Alternative Algorithm for Vehicle Routing Problem with Time Windows for Daily Deliveries

Ghani¹,

Shariff²,

Zahari³

2016

APM

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This study attempts to solve vehicle routing problem with time window (VRPTW). The study first identifies the real problems and suggests some recommendations on the issues. The technique used in this study is Genetic Algorithm (GA) and initialization applied is random population method. The objective of the study is to assign a number of vehicles to routes that connect customers and depot such that the overall distance travelled is minimized and the delivery operations are completed within the time windows requested by the customers. The analysis reveals that the problems experienced in vehicle routing with time window can be solved by GA and retrieved for optimal solutions. After a thorough study on VRPTW, it is highly recommended that a company should implement the optimal routes derived from the study to increase the efficiency and accuracy of delivery with time insertion.

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An improved differential evolution algorithm for vehicle routing problem with simultaneous pickups and deliveries and time windows

Cited by 123 publications

References 18 publications

Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem

Performansi Algoritma CODEQ dalam Penyelesaian Vehicle Routing Problem

Una Solución al Enrutamiento de Vehículos en Ciudades Montañosas Considerando Aspectos Ambientales y Económicos

An Alternative Algorithm for Vehicle Routing Problem with Time Windows for Daily Deliveries

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