A new VRPPD model and a hybrid heuristic solution approach for e-tailing

We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW

Revisión del estado del arte del problema de ruteo de vehículos con recogida y entrega (VRPPD)

This paper presents a literature review of the state of the art vehicle routing problem with deliveries and collections (VRPPD: Vehicle Routing Problem with pickups and deliveries). Is performed a classification of the different variants of the problem, and the work and conducted research on the subject according to its authors, according to the models and the solution methods used. Also are analyzed future trends in modeling and solution techniques. The VRPPD is a problem of type MILP (Mixed Integer Linear Programming) involving whole and continuous quantities, and that turns out to be NP-Hard problems with a medium or large number of customers. The research does emphasis on variants of the problem involving variables associated with the environment, and in particular reducing the impact of greenhouse gases. The review notes that published until 2016.En este trabajo se realiza una revisión bibliográfica del estado del arte del problema de ruteo de vehículos con entregas y recogidas (VRPPD: Vehicle routing problem with pickups and deliveries). Se presenta una clasificación de las diferentes variantes del problema, y de los trabajos e investigaciones realizados sobre el tema según sus autores, los modelos utilizados y los métodos de solución usados. También se analizan las tendencias futuras en modelamiento y técnicas de solución. El VRPPD es un problema del tipo MILP (programación lineal entera mixta) que involucra cantidades enteras y continuas, y que resulta ser NP-Hard en problemas con un número mediano o grande de clientes. En la búsqueda se hace énfasis en las variantes del problema que involucran variables asociadas al medio ambiente, y en particular con la reducción del impacto de gases de efecto invernadero. La revisión observa lo publicado hasta el año 2016

Vehicle routing problem with vendor selection, intermediate pick-ups and deliveries

Online shopping is becoming nowadays more indispensable to many people in their daily lives with a growing service range for a wide variety of goods. In this thesis, we study a distribution planning model for online retailers to fulfill the diverse consumer demands especially for premium goods, i.e. goods with a high potential to create additional income such as organic food, electronic materials, special gifts etc., without increasing inventory related costs. We refer to the related distribution planning problem as the Vehicle Routing Problem with Vendor Selection, Intermediate Pick-ups and Deliveries (VRPVSIPD). The VRPVSIPD is based on a distribution network where premium goods are acquired from a proper set of external vendors at multiple locations in the supply network and delivered to customers. In order to solve the VRPVSIPD, we present an improved Adaptive Large Neighborhood Search (ALNS) heuristic by introducing new removal, insertion and vendor selection/allocation algorithms. To investigate the performance of the proposed methodology, we conduct an extensive computational study using both the well-known Solomon instances for Vehicle Routing Problem with Time Windows and newly generated benchmark instances for the VRPVSIPD. Our results reveal that the proposed methodology is effective in terms of both the solution quality and computational time

Solución del problema de enrutamiento de vehículos con entregas y recogidas simultáneas : Una nueva matheurística

Este libro, producto de mi tesis doctoral, presenta una metodología para resolver el problema de enrutamiento de vehículos homogéneos con recogidas y entregas simultáneas (VRPSPD) utilizando matheurística formada por el algoritmo genético especializado Chu -Beasley y técnicas exactas de programación lineal de enteros mixtos, basadas en el procedimiento Branch -and- Bound, aplicado a la mejor configuración obtenida del algoritmo genético con el apoyo de métodos heurísticos constructivos en la determinación de los subproblemas, que hacen parte de la generación de la población inicial, necesaria en la etapa de mejora local. El problema considera un conjunto de clientes, cuyas demandas de recogida y entrega de productos o personas son conocidas, y cuyo objetivo es obtener el conjunto de rutas de costo mínimo, que permitan satisfacer la demanda de los clientes, considerando las respectivas limitaciones del sistema y los vehículos necesarios para completar el mismo. En su desarrollo se consideraron los siguientes aspectos: · Fundamentación teórica del problema de ruteo de vehículos con entregas y recogidas simultáneas. · Diseño metodológico para el desarrollo del contenido del libro. · Experimentos computacionales: La metodología desarrollada se implementa en C ++, y se utiliza un software de resolución CPLEX para encontrar la solución. La eficiencia de la implementación del algoritmo se verifica con el uso de instancias de prueba disponibles en la literatura especializada, obteniendo buenos resultados en las pruebas en tiempos de cómputo relativamente cortos

Inventory Routing Problem in Perishable Supply Chains: A Literature Review

Context: This paper presents a literature review of the Inventories Routing Problem (IRP) applied to supply chains of perishable products. Different approaches to solve this problem are identified and described in terms of structures, models and solution methods.  Method: A systematic literature review is conducted searching in different bibliographic databases and selecting the most relevant studies within the period 2004 to 2017. The results are analyzed so as to propose a taxonomy to classify and compare the different approaches proposed to address this problem. Results: We identified that the majority of studies consider heuristic-based algorithms to solve the problem. Because of its computational complexity the methods resort to metaheuristics and mateheuristics combined with exact methods. Regarding the application to specific supply chains of perishable products, they refer mostly to processed foods, medicines, and human blood. The constraints that differentiate this problem from other types of IRP are useful life and deterioration. Conclusions: The conditions and particularities of the supply chain of perishables products imply the need to consider new variables, parameters, constraints and objective functions; in the reviewed studies it is not clearly defined the differences involved when considering the perishability of the products in the supply chain. Future research should take into account the multiple ways in which deterioration is carried out with factors such as temperature, light, oxygen, humidity and in some cases microorganisms. Also include in the models the cold chain, hygiene standards, air pollution, emissions of greenhouse gases, generation of waste, occupation of roads and other aspects related to City Logistics and Green Logistics

El Problema de Ruteo e Inventarios en Cadenas de Suministro de Perecederos: Revisión de Literatura

Context: This paper presents a literature review of the Inventories Routing Problem (IRP) applied to supply chains of perishable products. Different approaches to solve this problem are identified and described in terms of structures, models and solution methods. Method: A systematic literature review is conducted searching in different bibliographic databases and selecting the most relevant studies within the period 2004 to 2017. The results are analyzed so as to propose a taxonomy to classify and compare the different approaches proposed to address this problem.Results: We identified that the majority of studies consider heuristic-based algorithms to solve the problem. Because of its computational complexity the methods resort to metaheuristics and mateheuristics combined with exact methods. Regarding the application to specific supply chains of perishable products, they refer mostly to processed foods, medicines, and human blood. The constraints that differentiate this problem from other types of IRP are useful life and deterioration.Conclusions: The conditions and particularities of the supply chain of perishables products imply the need to consider new variables, parameters, constraints and objective functions; in the reviewed studies it is not clearly defined the differences involved when considering the perishability of the products in the supply chain. Future research should take into account the multiple ways in which deterioration is carried out with factors such as temperature, light, oxygen, humidity and in some cases microorganisms. Also include in the models the cold chain, hygiene standards, air pollution, emissions of greenhouse gases, generation of waste, occupation of roads and other aspects related to City Logistics and Green Logistics. Contexto: Revisión de literatura del problema de ruteo e inventarios (IRP) aplicado a las cadenas de suministro de productos perecederos. Se identifican y describen los diferentes enfoques en cuanto a estructuras, modelos y métodos de solución.Método: Se realiza una revisión sistemática de la literatura en diferentes bases de datos bibliográficas y se plantea una taxonomía que clasifica las características de los estudios, lo anterior durante el período comprendido entre 2004 y 2017Resultados: Se encuentra que la mayoría de algoritmos propuestos son de carácter heurístico. Debido a complejidad computacional inherente al problema, se usan metaheurísticas y mateheurísticas combinadas con métodos exactos. Se aplican principalmente en alimentos, medicamentos y sangre humana. Las restricciones que diferencian de otros tipos de IRP son las de periodo de vida útil y deterioro.Conclusiones: Las condiciones y particularidades de la cadena de suministro de perecederos hace necesario que se planteen nuevas variables, parámetros, restricciones y funciones objetivo; por otro lado, en los estudios revisados no se establecen diferencias claras al involucrar la perecibilidad de los productos en los modelos. Las futuras investigaciones deberán tener en cuenta las múltiples maneras en las cuales se lleva a cabo el deterioro con factores como la temperatura, la luz, el oxígeno, la humedad y en algunos casos los microorganismos; asimismo, incluir en los modelos la cadena de frío, normas de higiene, contaminación del aire, emisiones de gases de efecto invernadero, generación de residuos, ocupación de vías y demás aspectos relacionados con city logistics y green logistics.

Constraint Programming-Based Heuristics for the Multi-Depot Vehicle Routing Problem with a Rolling Planning Horizon

Der Transportmarkt ist sowohl durch einem intensiven Kostenwettbewerb als auch durch hohe Erwartungen der Kunden an den Service geprägt. Die vorliegende Dissertation stellt zwei auf Constraint Programming basierende heuristische Frameworks vor, die eine Reoptimierung bereits geplanter Touren zu festgelegten Zeitpunkten erlauben und so eine Reaktion auf die gesteigerte Wettbewerbsdynamik und den Kostendruck ermöglichen.Actors on the transportation market currently face two contrary trends: Cost pressure caused by intense competition and a need for prompt service. We introduce two heuristic solution frameworks to enable freight carriers to deal with this situation by reoptimizing tours at predefined points in time. Both heuristics are based on Constraint Programming techniques

A vision-based optical character recognition system for real-time identification of tractors in a port container terminal

Automation has been seen as a promising solution to increase the productivity of modern sea port container terminals. The potential of increase in throughput, work efficiency and reduction of labor cost have lured stick holders to strive for the introduction of automation in the overall terminal operation. A specific container handling process that is readily amenable to automation is the deployment and control of gantry cranes in the container yard of a container terminal where typical operations of truck identification, loading and unloading containers, and job management are primarily performed manually in a typical terminal. To facilitate the overall automation of the gantry crane operation, we devised an approach for the real-time identification of tractors through the recognition of the corresponding number plates that are located on top of the tractor cabin. With this crucial piece of information, remote or automated yard operations can then be performed. A machine vision-based system is introduced whereby these number plates are read and identified in real-time while the tractors are operating in the terminal. In this paper, we present the design and implementation of the system and highlight the major difficulties encountered including the recognition of character information printed on the number plates due to poor image integrity. Working solutions are proposed to address these problems which are incorporated in the overall identification system.postprin

Job shop scheduling with artificial immune systems

The job shop scheduling is complex due to the dynamic environment. When the information of the jobs and machines are pre-defined and no unexpected events occur, the job shop is static. However, the real scheduling environment is always dynamic due to the constantly changing information and different uncertainties. This study discusses this complex job shop scheduling environment, and applies the AIS theory and switching strategy that changes the sequencing approach to the dispatching approach by taking into account the system status to solve this problem. AIS is a biological inspired computational paradigm that simulates the mechanisms of the biological immune system. Therefore, AIS presents appealing features of immune system that make AIS unique from other evolutionary intelligent algorithm, such as self-learning, long-lasting memory, cross reactive response, discrimination of self from non-self, fault tolerance, and strong adaptability to the environment. These features of AIS are successfully used in this study to solve the job shop scheduling problem. When the job shop environment is static, sequencing approach based on the clonal selection theory and immune network theory of AIS is applied. This approach achieves great performance, especially for small size problems in terms of computation time. The feature of long-lasting memory is demonstrated to be able to accelerate the convergence rate of the algorithm and reduce the computation time. When some unexpected events occasionally arrive at the job shop and disrupt the static environment, an extended deterministic dendritic cell algorithm (DCA) based on the DCA theory of AIS is proposed to arrange the rescheduling process to balance the efficiency and stability of the system. When the disturbances continuously occur, such as the continuous jobs arrival, the sequencing approach is changed to the dispatching approach that involves the priority dispatching rules (PDRs). The immune network theory of AIS is applied to propose an idiotypic network model of PDRs to arrange the application of various dispatching rules. The experiments show that the proposed network model presents strong adaptability to the dynamic job shop scheduling environment.postprin

A new VRPPD model and a hybrid heuristic solution approach for e-tailing

We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where ‘‘premium’’ goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitatedVRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW