Optimization of LPG Distribution Route Using Variable Neighborhood Tabu Search Algorithm

PT. Galaxi Energi Pratama (GEP) is one of the biggest distributors of subsidized LPG in Malang Raya area. Currently the route planning is not done very well, which results in a high fuel cost. With the company's main business process being distribution, the planning needs to be improved to maximize the profit. The problem in PT. GEP is classified as the Heterogeneous Vehicle Routing Problem with Multiple Trips (HVRPM). This problem is classified as NP-Hard and requires high computational effort to obtain a good solution so metaheuristic method is preferred. In this research, variable neighborhood tabu search (VNTS) algorithm is developed to solve the HVRPM and implemented to minimize the fuel cost of PT. GEP. The developed algorithm is implemented in the six instances collected from the case study. The generated trips produce a total savings of Rp 150,876 for one operational week, or roughly 18% of the initial cost. The computation time of the algorithm is evaluated by comparing with Simulated Annealing using a problem with the same size. VNTS has a lower average time and is expected to perform competitively when a standardized dataset is used for comparison. The solution quality of the algorithm is then compared with branch-and-bound method. VNTS is able to find one global optimal solution out of the six instances and overall, it performs better than branch-and-bound

Optimización basada en metaheurísticas: una aproximación a la solución del problema de ruteo de vehículos con ventanas horarias

Los problemas complejos que se presentan en las organizaciones han sido tema de estudio durante las últimas décadas debido a su alto impacto en los resultados empresariales. Las decisiones tomadas por los líderes de los procesos respecto a estos problemas generalmente se basan en su intuición, forjada por experiencias, perjuicios y patrones mentales, considerados como correctos, omitiendo cualquier intento de análisis cuantitativo por el alto número de variables y la existencia de varios objetivos que se interponen entre sí. La planeación de las rutas de una flota de transporte para la entrega de mercancías es catalogado como una operación de alta complejidad, por el número de soluciones posibles, la interconexión de múltiples objetivos y un gran número de variables que se aumenta de forma exponencial en el momento que se añaden ventanas horarias. El problema de ruteo con ventanas horarias es crítico a la hora de tomar decisiones estratégicas en la industria por su relación con el costo logístico total. Por la importancia y desconocimiento de este problema en las organizaciones, el objetivo de este artículo es describir y caracterizar los diferentes métodos de solución, para que de esta manera los líderes en logística cuenten con un conocimiento técnico de las herramientas disponibles para optimizar sus procesos de transporte y mediante un análisis numérico, basados en su intuición y experiencia, logren generar los mejores resultados de una manera rápida y eficaz.Organization´s complex problems have been studied during the last decades, due his high impact in the business results. Taken decisions by the processes’ leaders related with these problems are based on their intuition, created by experiences, bias and mental patterns. Avoid any attempt of quantitative analysis for the high number of variables and objectives that stand between each other. Planning routing fleet of vehicles for the delivering of goods, it’s a high complex operation, for the number of possible solutions, multi-objective principles and a large number of variables, increased with time windows. The vehicle routing problem with time windows is a regular operation in retailer companies and it is critical for the decision-making in the industry, for his relation with logistics costs. Exacts methods was the first tools created for find the optimal solution, inefficient strategy due the problem’s nature. Trough advances in the optimization field, emerged exploration methods, known as heuristics and metaheuristics. For the importance and lack of awareness of this problem in organizations, the objective of this article is describing the different methods of solution. In this way the logistic leaders have a technical knowledge about the available tools for optimize their transport processes and by numerical analysis, based on their intuition and experience, achieves the best results in an efficient way

Urban Logistics in Amsterdam: A Modal Shift from Roadways to Waterway

The efficiency of urban logistics is vital for economic prosperity and quality of life in cities. However, rapid urbanization poses significant challenges, such as congestion, emissions, and strained infrastructure. This paper addresses these challenges by proposing an optimal urban logistic network that integrates urban waterways and last-mile delivery in Amsterdam. The study highlights the untapped potential of inland waterways in addressing logistical challenges in the city center. The problem is formulated as a two-echelon location routing problem with time windows, and a hybrid solution approach is developed to solve it effectively. The proposed algorithm consistently outperforms existing approaches, demonstrating its effectiveness in solving existing benchmarks and newly developed instances. Through a comprehensive case study, the advantages of implementing a waterway-based distribution chain are assessed, revealing substantial cost savings (approximately 28%) and reductions in vehicle weight (about 43%) and travel distances (roughly 80%) within the city center. The incorporation of electric vehicles further contributes to environmental sustainability. Sensitivity analysis underscores the importance of managing transshipment location establishment costs as a key strategy for cost efficiencies and reducing reliance on delivery vehicles and road traffic congestion. This study provides valuable insights and practical guidance for managers seeking to enhance operational efficiency, reduce costs, and promote sustainable transportation practices. Further analysis is warranted to fully evaluate the feasibility and potential benefits, considering infrastructural limitations and canal characteristics

A local branching algorithm applied to the inventory routing problem with time-windows

Orientador: Prof. Dr. Cassius Tadeu ScarpinDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Programa de Pós-Graduação em Gestão de Organizações, Liderança e Decisão. Defesa : Curitiba, 25/11/2021Inclui referênciasResumo: O ininterrupto desenvolvimento de novas tecnologias e ferramentas para o controle e simulação de processos, aliado à constante busca por modelos matemáticos mais precisos e representativos da realidade, tem possibilitado uma aproximação entre teoria e prática inédita na operação de cadeias de suprimentos. Plan ejamentos táticos e operacionais de alta acurácia são essenciais para determinados tipos de operações, como por exemplo em empresas de entrega de bens perecíveis e de distribuição de combustíveis. Além da preocupação com o controle eficiente de seus estoqu es e de suas frotas veiculares, seus clientes devem ser atendidos dentro de intervalos de tempo determinados, de modo a atingir níveis de serviço estabelecidos e até mesmo garantir a viabilidade de seus produtos. Mesmo com os avanços expressivos na área da modelagem de sistemas de roteamento de veículos, alguns desafios na resolução destes problemas ainda persistem. Este trabalho propõe um modelo matemático de Programação Linear Inteira Mista (PLIM) para o Problema de Roteamento de Estoque com Janelas de Tempo (Inventory-Routing Problem with Time-Windows - IRPTW). Um modelo exato é elaborado, sendo testado seu desempenho computacional sob o auxílio de dois conjuntos de desigualdades válidas desenvolvidas para o Problema de Roteamento de Estoque (Inventory-Routing Problem - IRP), variadas técnicas de préprocessamento, heurísticas de melhoria de solução, e um algoritmo de Local branching. Uma configuração utilizando desigualdades válidas referentes a limites melhorados proporciona os melhores resultados dentre todas as avaliadas. Esta configuração é usada como base para o algoritmo de Local Branching, que apresenta modificações específicas para a exploração agressiva e rápida de vizinhanças reduzidas do espaço de busca do problema. Os resultados obtidos são comparados com um grupo de instâncias desenvolvido para o problema, apresentando ganhos consistentes quando comparado aos resultados existentes. Diversas novas melhores soluções são encontradas para o conjunto avaliado e estabelecem-se limites superiores e inferiores (gaps) para diversas outras instâncias. Este trabalho, até onde sabemos, é o primeiro a integrar todas essas ferramentas de otimização para a resolução do IRPTW, e é o primeiro a comparar resultados com um conjunto de instâncias exclusivamente desenvolvido para o IRPTW, ao mesmo tempo que expande este grupo com instâncias ainda mais complexas. A estratégia focada em exploração parcial de vizinhanças do Local Branching também é uma contribuição, podendo ser ainda mais aprofundada e melhorada em trabalhos futuros.Abstract: The continuous development of new technologies and tools for better process control and simulation, combined with the strive for better and more representative mathematical models, has allowed supply chain models to reach levels of accuracy never seen. Tactical and operational planning are essential to the operation of many logistic chains, such as perishable products delivery and fuel distribution. Not only these companies have to efficiently manage their inventories and vehicle fleets to achieve predetermined levels of service, they must also fulfill their customers' needs in restricted time-windows and guarantee their product's viability during the entire delivery process. Even though many improvements were made in the field of vehicle routing, some challenges remain. This dissertation proposes a mixed-integer programming (MIP) model for the Inventory-Routing Problem with Time-Windows (IRPTW). An exact model is proposed and has its performance, alongside two groups of valid inequalities developed for the Inventory-Routing Problem (IRP), different preprocessing techniques, solution improvement heuristics, and a Local Branching algorithm, analyzed. A configuration with inventory control valid inequalities presented the best results between all analyzed configurations. This configuration is used as a basis for the Local Branching algorithm, which is specifically adapted to explore reduced neighborhoods of the problem's search space quickly and aggressively. The model is tested using a benchmark instance set and is shown to be superior in comparison to the existing results. Several new best-known solutions are determined for the instance set, just as new upper and lower bounds (gaps) are determined for several other instances. The developments presented here are, as far as we know, the first ones to integrate all these tools under one optimization framework for the IRPTW. This dissertation is also the first one to compare results with a benchmark instance set developed specifically for the problem, while also expanding said instance set. The partial neighborhood exploration used by the Local Branching algorithm is also a contribution to the literature since it enables a quick and efficient exploration of the method's tree. This integration of optimization tools can be worked on future papers, having its approach refined to provide even better results

Aplicación de un algoritmo memético al problema de planificación de la producción en fabricación aditiva considerando orientaciones alternativas en las piezas

El estudio realizado se ha basado en la experimentación de instancias de problemas de fabricación aditiva para la optimización de costes del problema de planificación de la producción basado en la asignación de piezas a estructuras para ser fabricadas en máquinas de impresión en 3D. El problema ha considerado la posibilidad de incorporar diferentes orientaciones en las piezas a introducir aumentado la complejidad del problema y acercándose a una situación real en la industria. Esta componente de orientaciones extra permite reducir los costes totales de producción sobre todo en problemas de gran complejidad. Para la resolución de este problema, se utiliza un algoritmo memético compuesto por la hibridación de un algoritmo de Sistema de Colonia de Hormigas y un algoritmo de Búsqueda Descendente en Entornos Variables (VND) para la búsqueda local. . Con el fin de obtener una solución inicial al problema, se ha desarrollado previamente una heurística de inserción semiparalela. Estos método son de gran interés científico actualmente pero no han sido evaluados hasta ahora de esta manera en los problemas de fabricación aditiva permitiendo varias orientaciones a las piezas. Ha sido necesario encontrar los valores óptimos para la heurística semiparalela en una experimentación previa para reducir los tiempos de ejecución. Posteriormente se ha comprobado la efectividad de la búsqueda local realizando una comparación de los resultados obtenidos analizado el uso en solitario del ACS sin postprocesado respecto al Mem-ACS completo. La comparación de resultados se ha analizado para los problemas considerando 1, 2 y 3 orientaciones y se ha comprobado que el Mem-ACS ofrece mejores resultados de coste para problemas que aumentan su complejidad computacional. Esta complejidad está marcada por el número de piezas, número de orientaciones disponibles y número de máquinas paralelas utilizadas.The study carries out the experimentation of additive manufacturing problem instances based on cost optimisation over production problems collected and augmented from the literature review. It is based on the assignment of parts to structures in order to be manufactured on 3D printing machines. The problem has considered the possibility of several orientations for each part to be introduced. This characteristic increases the complexity of the problem, and it approaches the study to a real situation in the industry. This component of extra orientations allows reducing the total production costs of the production lines especially in problems of high complexity. A memetic algorithm composed of an initial phase of semi-parallel heuristics is used to provide the initial solution and continues with the optimisation phase by using the Ant Colony System algorithm. It is lates post-processed by a local VND search. These methods are nowadays of great scientific interest but have not been evaluated so far within the additive manufacturing problems allowing various part orientations. It has been necessary to find the optimal values for the semi-parallel heuristic in a previous experimentation in order to reduce execution times. Subsequently, the use of the ACS alone without post-processing has been analysed and compared to the complete Mem-ACS. The study results in better cost results by using Mem-ACS for problems that increase their computational complexity considering 1, 2 and 3 orientations. This complexity is measured by the number of parts, the number of available orientations and the number of parallel machines used.Universidad de Sevilla. Máster en Organización Industrial y Gestión de Empresa

Heuristic approaches for flight and maintenance planning of large fleets

The nature of military helicopter operations scheduling is such that replanning occurs on a regular basis. With this as a requirement, any solution that takes more than a day to compute is unacceptable. We have shown that this time constraint mitigates against the generation of truly optimum solution using integer programming. Computationally faster, near optimal solutions are a fundamental practical requirement, but the cost of helicopter operations, like that of any aircraft fleet, is large and any sub-optimality will result in substantial cost or operational effectiveness penalties. This research has shown that heuristic, meta-heuristic, and their hybrids can make a computationally difficult problem tractable to the level acceptable for solving real lift problem complexities. The result indicate that the computationally fast approaches developed are inevitable sub-optimal but maintain enough quality to significantly improve upon current approaches to FMP and are practically useful

New variants of variable neighbourhood search for 0-1 mixed integer programming and clustering

Many real-world optimisation problems are discrete in nature. Although recent rapid developments in computer technologies are steadily increasing the speed of computations, the size of an instance of a hard discrete optimisation problem solvable in prescribed time does not increase linearly with the computer speed. This calls for the development of new solution methodologies for solving larger instances in shorter time. Furthermore, large instances of discrete optimisation problems are normally impossible to solve to optimality within a reasonable computational time/space and can only be tackled with a heuristic approach. In this thesis the development of so called matheuristics, the heuristics which are based on the mathematical formulation of the problem, is studied and employed within the variable neighbourhood search framework. Some new variants of the variable neighbourhood searchmetaheuristic itself are suggested, which naturally emerge from exploiting the information from the mathematical programming formulation of the problem. However, those variants may also be applied to problems described by the combinatorial formulation. A unifying perspective on modern advances in local search-based metaheuristics, a so called hyper-reactive approach, is also proposed. Two NP-hard discrete optimisation problems are considered: 0-1 mixed integer programming and clustering with application to colour image quantisation. Several new heuristics for 0-1 mixed integer programming problem are developed, based on the principle of variable neighbourhood search. One set of proposed heuristics consists of improvement heuristics, which attempt to find high-quality near-optimal solutions starting from a given feasible solution. Another set consists of constructive heuristics, which attempt to find initial feasible solutions for 0-1 mixed integer programs. Finally, some variable neighbourhood search based clustering techniques are applied for solving the colour image quantisation problem. All new methods presented are compared to other algorithms recommended in literature and a comprehensive performance analysis is provided. Computational results show that the methods proposed either outperform the existing state-of-the-art methods for the problems observed, or provide comparable results. The theory and algorithms presented in this thesis indicate that hybridisation of the CPLEX MIP solver and the VNS metaheuristic can be very effective for solving large instances of the 0-1 mixed integer programming problem. More generally, the results presented in this thesis suggest that hybridisation of exact (commercial) integer programming solvers and some metaheuristic methods is of high interest and such combinations deserve further practical and theoretical investigation. Results also show that VNS can be successfully applied to solving a colour image quantisation problem.EThOS - Electronic Theses Online ServiceMathematical Institute, Serbian Academy of Sciences and ArtsGBUnited Kingdo

Algorithms for vehicle routing problems with heterogeneous fleet, flexible time windows and stochastic travel times

Orientador: Vinícius Amaral ArmentanoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Este trabalho aborda três variantes multiatributo do problema de roteamento de veículos. A primeira apresenta frota heterogênea, janelas de tempo invioláveis e tempos de viagem determinísticos. Para resolvê-la, são propostos algoritmos ótimos baseados na decomposição de Benders. Estes algoritmos exploram a estrutura do problema em uma formulação de programação inteira mista, e três diferentes técnicas são desenvolvidas para acelerá-los. A segunda variante contempla os atributos de frota heterogênea, janelas de tempo flexíveis e tempos de viagem determinísticos. As janelas de tempo flexíveis permitem o início do serviço nos clientes com antecipação ou atraso limitados em relação às janelas de tempo invioláveis, com custos de penalidade. Este problema é resolvido por extensões dos algoritmos de Benders, que incluem novos algoritmos de programação dinâmica para a resolução de subproblemas com a estrutura do problema do caixeiro viajante com janelas de tempo flexíveis. A terceira variante apresenta frota heterogênea, janelas de tempo flexíveis e tempos de viagem estocásticos, sendo representada por uma formulação de programação estocástica inteira mista de dois estágios com recurso. Os tempos de viagem estocásticos são aproximados por um conjunto finito de cenários, gerados por um algoritmo que os descreve por meio da distribuição de probabilidade Burr tipo XII, e uma matheurística de busca local granular é sugerida para a resolução do problema. Extensivos testes computacionais são realizados em instâncias da literatura, e as vantagens das janelas de tempo flexíveis e dos tempos de viagem estocásticos são enfatizadasAbstract: This work addresses three multi-attribute variants of the vehicle routing problem. The first one presents a heterogeneous fleet, hard time windows and deterministic travel times. To solve this problem, optimal algorithms based on the Benders decomposition are proposed. Such algorithms exploit the structure of the problem in a mixed-integer programming formulation, and three algorithmic enhancements are developed to accelerate them. The second variant comprises a heterogeneous fleet, flexible time windows and deterministic travel times. The flexible time windows allow limited early and late servicing at customers with respect to their hard time windows, at the expense of penalty costs. This problem is solved by extensions of the Benders algorithms, which include novel dynamic programming algorithms for the subproblems with the special structure of the traveling salesman problem with flexible time windows. The third variant presents a heterogeneous fleet, flexible time windows and stochastic travel times, and is represented by a two-stage stochastic mixed-integer programming formulation with recourse. The stochastic travel times are approximated by a finite set of scenarios generated by an algorithm which describes them using the Burr type XII distribution, and a granular local search matheuristic is suggested to solve the problem. Extensive computational tests are performed on instances from the literature, and the advantages of flexible windows and stochastic travel times are stressed.DoutoradoAutomaçãoDoutor em Engenharia Elétrica141064/2015-3CNP

Diseño y aplicación de una herramienta para la optimización de rutas de vehículos con aspectos medioambientales

En la actualidad, en torno al 90% de la población de la Unión Europea se encuentra expuesta a altas concentraciones de algunos de los contaminantes atmosféricos más nocivos para la salud, reduciendo la esperanza de vida de la población y ocasionando un fuerte impacto económico en el producto interior bruto de los países. Dentro de los sectores económicos, el transporte se presenta como una de las principales fuentes de contaminación ya que genera niveles nocivos de emisiones contaminantes y es el responsable de hasta el 24% de las emisiones de gases de efecto invernadero (GEI) en la Unión Europea. Estas emisiones dependen en gran medida de los combustibles utilizados, de la carga y tecnología del motor de los vehículos y principalmente de las distancias recorridas. El problema de la distribución de productos desde los almacenes a los usuarios finales juega un papel central en la gestión de algunos sistemas logísticos, donde la determinación de rutas de reparto eficientes es fundamental en la reducción de costes. Este problema en la vida real, se caracteriza por disponer las empresas de distribución de una flota heterogénea, en la que vehículos con diferentes características son incorporados a lo largo del tiempo para una mejor adaptación a las demandas de los clientes. Entre las características más destacadas se encuentran vehículos con diferentes capacidades y antigüedad, usos de combustibles alternativos y tecnología del motor. Por todo ello, en el contexto actual la componente medioambiental tiene que ser añadida en el proceso de toma de decisiones a las estrategias logísticas tradicionales, basadas en costes y tiempos. Esta Tesis Doctoral se ha centrado en su mayor parte al desarrollo de nuevos modelos y algoritmos para la resolución del Problema de Enrutamiento de Vehículos con Flota Fija Heterogénea y Ventanas de Tiempo (HVRPTW), con la consideración adicional de reducir las emisiones de GEI y de partículas contaminantes. La formulación del problema se realiza desde dos perspectivas muy diferenciadas. La primera de ellas incorpora una metodología basada en la estimación de los costes asociados a las externalidades presentes en las actividades del transporte. La segunda perspectiva comprende técnicas de optimización multiobjetivo con asignación de preferencias a priori, en el que el decisor puede establecer sus preferencias por adelantado. La elaboración de las rutas eco-eficientes se plantea mediante modelos lineales de programación matemática y se resuelve usando técnicas cuantitativas. Estas técnicas comprenden algoritmos heurísticos y metaheurísticos que combinan diversos procedimientos avanzados para tratar la complejidad del problema. En particular, esta Tesis describe una heurística de inserción secuencial semi-paralela y una metaheurística híbrida de búsqueda de entorno variable descendente con búsqueda tabú y lista de espera, que introduce una mayor flexibilidad para la resolución de cualquier variante del problema HVRPTW. Los algoritmos han sido aplicados a problemas típicos de recogida y reparto de mercancías de la literatura científica y a un caso real, que comprende la planificación de rutas y personal en una empresa de servicios con características y restricciones muy peculiares. Los resultados demuestran que el algoritmo resuelve de manera eficiente la variante del problema abordado y es extensible para la resolución de otras variantes. El resultado de la Tesis es el desarrollo de una herramienta para la ayuda a la toma de decisiones en el diseño y control de rutas eco-eficientes. Dicha herramienta podrá integrarse con el sistema de información geográfica (GIS) particular de cada empresa y permitirá la visualización de las rutas eco-eficientes, evaluando el impacto producido en los ámbitos económico, energético, operativo y medioambiental. Por ello, la herramienta tendrá un impacto económico directo sobre los usuarios finales y permitirá la comparación de rutas y resultados obtenidos a partir de diferentes alternativas, logrando una mayor competitividad y el cumplimiento de los compromisos de sostenibilidad en la empresa. Por otro lado, a nivel global, la herramienta contribuye a una mejora social derivada de una reducción del consumo energético y de una disminución de las emisiones contaminantes de las flotas de transporte de mercancías por carretera, que tienen un impacto a nivel local, nacional e internacional. En este sentido, la Tesis Doctoral contribuye claramente al desarrollo estratégico del sector transporte de mercancías, aumentando la eficiencia de las flotas de transporte por carretera y logrando una mayor sostenibilidad y competitividad.Nowadays, around 90% of city dwellers in the European Union are exposed to high concentrations of healthharmful pollutants, reducing the life expectancy of the population and having a large impact on the gross domestic product of European countries. Among the economic sectors, transport is presented as one of the main sources of pollution because it generates harmful levels of emissions and is responsible for up to 24% of greenhouse gases (GHG) emissions in the European Union. These emissions depend heavily on the fuel type used, the carried load, the engine technology and the total distance covered. The problem of the distribution of goods from warehouses to end users plays a central role in the logistics systems management, where the design of efficient routes is critical in reducing costs. This real-life problem is characterized by presenting a heterogeneous fleet where vehicles with different features are incorporated over the time for a better adaptation to the changing customer demands. These features include vehicles with different capacities and age, alternative fuels and motor technologies. Therefore, in the present context, environmental targets are to be added to traditional logistics strategies based on cost and time in the decision making process. The research of this Thesis has focused on the development of new mathematical models and algorithms for solving the Fixed Fleet Heterogeneous Vehicle Routing Problem with Time Windows (HVRPTW) with the additional consideration of reducing GHG and pollutants emissions. The formulation of the problem is made from two different perspectives. The first incorporates a methodology based on the estimation of the external costs of transport activities. The second perspective comprises a multiobjective optimization method with a priori articulation of preferences, in which the decision maker can establish the preferences in advance. The design of eco-efficient routes is proposed by linear mathematical programming models and is solved using quantitative techniques. These techniques include heuristics and metaheuristics that combine various advanced procedures to deal with the complexity of the problem. In particular, this Thesis describes a semi-parallel insertion heuristic and a hybrid variable neighborhood descent metaheuristic based on a tabu search algorithm for the local search and a holding list that achieves flexibility for solving any HVRPTW variant. The algorithms have been applied to benchmark problems from the scientific literature and to a real-world case that deals with a routing and scheduling problem in a service company with particular characteristics and constraints. The results show that the algorithm efficiently solves the problem addressed and it can be extended to other problem variants. The result of the Thesis is the development of a decision making process tool aimed to help in the design and control of eco-efficient routes. This tool can be integrated with the particular geographic information system (GIS) of each company, allowing the display of eco-efficient routes and assessing the economic, energy, operational and environmental impacts. Therefore, the tool will have an economic impact on the end users, with a comparison of the final routes and the results obtained from different alternatives, achieving greater competitiveness and fulfilling the sustainability commitments in the company. On the other hand, the tool globally contributes to a social improvement resulting from the fuel consumption and pollutant emissions reductions from road transport, which have an impact at local, national and international level. In this sense, the Thesis clearly contributes to the strategic development of the transport sector, increasing the efficiency of road transport fleets and achieving greater sustainability and competitiveness