On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

OPTIMIZATION OF RAILWAY TRANSPORTATION HAZMATS AND REGULAR COMMODITIES

Transportation of dangerous goods has been receiving more attention in the realm of academic and scientific research during the last few decades as countries have been increasingly becoming industrialized throughout the world, thereby making Hazmats an integral part of our life style. However, the number of scholarly articles in this field is not as many as those of other areas in SCM. Considering the low-probability-and-high-consequence (LPHC) essence of transportation of Hazmats, on the one hand, and immense volume of shipments accounting for more than hundred tons in North America and Europe, on the other, we can safely state that the number of scholarly articles and dissertations have not been proportional to the significance of the subject of interest. On this ground, we conducted our research to contribute towards further developing the domain of Hazmats transportation, and sustainable supply chain management (SSCM), in general terms. Transportation of Hazmats, from logistical standpoint, may include all modes of transport via air, marine, road and rail, as well as intermodal transportation systems. Although road shipment is predominant in most of the literature, railway transportation of Hazmats has proven to be a potentially significant means of transporting dangerous goods with respect to both economies of scale and risk of transportation; these factors, have not just given rise to more thoroughly investigation of intermodal transportation of Hazmats using road and rail networks, but has encouraged the competition between rail and road companies which may indeed have some inherent advantages compared to the other medium due to their infrastructural and technological backgrounds. Truck shipment has ostensibly proven to be providing more flexibility; trains, per contra, provide more reliability in terms of transport risk for conveying Hazmats in bulks. In this thesis, in consonance with the aforementioned motivation, we provide an introduction into the hazardous commodities shipment through rail network in the first chapter of the thesis. Providing relevant statistics on the volume of Hazmat goods, number of accidents, rate of incidents, and rate of fatalities and injuries due to the incidents involving Hazmats, will shed light onto the significance of the topic under study. As well, we review the most pertinent articles while putting more emphasis on the state-of-the-art papers, in chapter two. Following the discussion in chapter 3 and looking at the problem from carrier company’s perspective, a mixed integer quadratically constraint problem (MIQCP) is developed which seeks for the minimization of transportation cost under a set of constraints including those associating with Hazmats. Due to the complexity of the problem, the risk function has been piecewise linearized using a set of auxiliary variables, thereby resulting in an MIP problem. Further, considering the interests of both carrier companies and regulatory agencies, which are minimization of cost and risk, respectively, a multiobjective MINLP model is developed, which has been reduced to an MILP through piecewise linearization of the risk term in the objective function. For both single-objective and multiobjective formulations, model variants with bifurcated and nonbifurcated flows have been presented. Then, in chapter 4, we carry out experiments considering two main cases where the first case presents smaller instances of the problem and the second case focuses on a larger instance of the problem. Eventually, in chapter five, we conclude the dissertation with a summary of the overall discussion as well as presenting some comments on avenues of future work

Metaheuristic Algorithm for Solving Biobjective Possibility Planning Model of Location-Allocation in Disaster Relief Logistics

Thousands of victims and millions of affected people are hurt by natural disasters every year. Therefore, it is essential to prepare proper response programs that consider early activities of disaster management. In this paper, a multiobjective model for distribution centers which are located and allocated periodically to the damaged areas in order to distribute relief commodities is offered. The main objectives of this model are minimizing the total costs and maximizing the least rate of the satisfaction in the sense of being fair while distributing the items. The model simultaneously determines the location of relief distribution centers and the allocation of affected areas to relief distribution centers. Furthermore, an efficient solution approach based on genetic algorithm has been developed in order to solve the proposed mathematical model. The results of genetic algorithm are compared with the results provided by simulated annealing algorithm and LINGO software. The computational results show that the proposed genetic algorithm provides relatively good solutions in a reasonable time

Solving the waste collection problem from a multiobjective perspective: New methodologies and case studies

Fecha de lectura Tesis Doctoral: 19 de marzo de 2018.Economía Aplicada ( Matemáticas) Resumen tesis: El tratamiento de residuos es un tema de estudio por parte de las administraciones locales a nivel mundial. Distintos factores han de tenerse en cuenta para realizar un servicio eficiente. En este trabajo se desarrolla una herramienta para analizar y resolver el problema de la recogida de residuos sólidos en Málaga. Tras un análisis exhaustivo de los datos, se aborda el problema real como un problema de rutas multiobjetivo con capacidad limitada. Para los problemas multiobjetivo, no suele existir una única solución óptima, sino un conjunto de soluciones eficientes de Pareto. Las características del problema hacen inviable su resolución de forma exacta, por lo que se aplican distintas estrategias metaheurísticas para obtener una buena aproximación. En particular, se combinan las técnicas de GRASP, Path Relinking y Variable Neighborhood Search, que son adaptadas a la perspectiva multicriterio. Se trata de una aproximación en dos fases: una primera aproximación de la frontera eficiente se genera mediante un GRASP multiobjetivo. Tres son los métodos propuestos para la primera aproximación, dos de ellos derivados de la publicación de Martí et al. (2015) y el último se apoya en la función escalarizada de logro de Wierzbicki (Wierzbicki, 1980) para distintas combinaciones de pesos. A continuación, esta aproximación es mejorada con una versión de Path Relinking o Variable Neighborhood Search, con un punto de referencia diseñado para problemas multiobjetivo. Una vez generada la aproximación de la frontera eficiente, el proceso de obtención de la solución que más se adecúa a las preferencias de los gestores se basa en el desarrollo de un método interactivo sin trade – off, derivado de la filosofía NAUTILUS (Miettinen et al. 2010). Para evitar gastos de cómputo extensos, esta metodología se apoya en una pre - computación de los elementos de la frontera eficiente

A review of multi-objective optimization of container flow using sea and land legs together

Intermodalni transport je sistem koji podrazumeva prevoz 'od vrata do vrata' pod odgovornošću jednog prevoznika tj. operatora intermodalnog transporta, uz učešće najmanje dva vida transporta (u prevozu tereta bez promene tovarno manipulativne jedinice). Kontejnerski transport je glavna komponenta intermodalnog transporta i međunarodne trgovine. Kontejnerski transportni tok bi trebalo da bude optimalan kako bi se osiguralo pravilno korišćenje resursa i kako bi se omogućila profitabilnost korisnika. Razni višekriterijumski evolucioni algoritmi su razvijeni da efikasno reše probleme optimizacije u kontejnerskom transportu. Ovaj rad predstavlja kratak pregled problema optimizacije u intermodalnom transportu posmatrajući jedan transportni lanac u kome se transport kontejnera obavlja morem i kopnom uzimajući u obzir tri najčešće razmatrana optimizaciona kriterijuma (transportni troškovi, tranzitno vreme i emisija ugljen-dioksida).Intermodal freight transportation refers to a multi-modal chain of container-transportation services which usually links the initial shipper to the final consignee of the container (door-to-door service) and takes place over long distances. Container transportation is a major component of intermodal transportation and international commerce. Container flow should be optimal to ensure proper resource utilization and profitability to players. Various multi-objective evolutionary algorithms have been developed to efficiently solve optimization problems in container flows. This paper presents a short review of optimization problems in intermodal transport using sea and land legs together regarding three mostly observed objectives (transport cost, transit time and CO2 emissions)

Network design decisions in supply chain planning

Structuring global supply chain networks is a complex decision-making process. The typical inputs to such a process consist of a set of customer zones to serve, a set of products to be manufactured and distributed, demand projections for the different customer zones, and information about future conditions, costs (e.g. for production and transportation) and resources (e.g. capacities, available raw materials). Given the above inputs, companies have to decide where to locate new service facilities (e.g. plants, warehouses), how to allocate procurement and production activities to the variousmanufacturing facilities, and how to manage the transportation of products through the supply chain network in order to satisfy customer demands. We propose a mathematical modelling framework capturing many practical aspects of network design problems simultaneously. For problems of reasonable size we report on computational experience with standard mathematical programming software. The discussion is extended with other decisions required by many real-life applications in strategic supply chain planning. In particular, the multi-period nature of some decisions is addressed by a more comprehensivemodel, which is solved by a specially tailored heuristic approach. The numerical results suggest that the solution procedure can identify high quality solutions within reasonable computational time

A review of multi-objective optimization of container flow using sea and land legs together

Intermodalni transport je sistem koji podrazumeva prevoz 'od vrata do vrata' pod odgovornošću jednog prevoznika tj. operatora intermodalnog transporta, uz učešće najmanje dva vida transporta (u prevozu tereta bez promene tovarno manipulativne jedinice). Kontejnerski transport je glavna komponenta intermodalnog transporta i međunarodne trgovine. Kontejnerski transportni tok bi trebalo da bude optimalan kako bi se osiguralo pravilno korišćenje resursa i kako bi se omogućila profitabilnost korisnika. Razni višekriterijumski evolucioni algoritmi su razvijeni da efikasno reše probleme optimizacije u kontejnerskom transportu. Ovaj rad predstavlja kratak pregled problema optimizacije u intermodalnom transportu posmatrajući jedan transportni lanac u kome se transport kontejnera obavlja morem i kopnom uzimajući u obzir tri najčešće razmatrana optimizaciona kriterijuma (transportni troškovi, tranzitno vreme i emisija ugljen-dioksida).Intermodal freight transportation refers to a multi-modal chain of container-transportation services which usually links the initial shipper to the final consignee of the container (door-to-door service) and takes place over long distances. Container transportation is a major component of intermodal transportation and international commerce. Container flow should be optimal to ensure proper resource utilization and profitability to players. Various multi-objective evolutionary algorithms have been developed to efficiently solve optimization problems in container flows. This paper presents a short review of optimization problems in intermodal transport using sea and land legs together regarding three mostly observed objectives (transport cost, transit time and CO2 emissions)