Optimisation of a distribution system in the retail industry: An Australian retail industry

This paper develops a mathematical model based on inventory routing problem that aims to minimise transportation cost, inventory carrying cost and optimises delivery schedules in a retail Australian industry. A supply chain is considered which comprises of a single distribution centre, having homogenous fleet of vehicles, supplying a single product to multiple retailers having deterministic demand. The mathematical model takes into account varying level of road congestion.N/

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.

Decision support modeling for sustainable food logistics management

Summary For the last two decades, food logistics systems have seen the transition from traditional Logistics Management (LM) to Food Logistics Management (FLM), and successively, to Sustainable Food Logistics Management (SFLM). Accordingly, food industry has been subject to the recent challenges of reducing the amount of food waste and raising energy efficiency to reduce greenhouse gas emissions. These additional challenges add to the complexity of logistics operations and require advanced decision support models which can be used by decision makers to develop more sustainable food logistics systems in practice. Hence, the overall objective of this thesis was to obtain insight in how to improve the sustainability performance of food logistics systems by developing decision support models that can address the concerns for transportation energy use and consequently carbon emissions, and/or product waste, while also adhering to competitiveness. In line with this overall objective, we have defined five research objectives. The first research objective (RO), which is to identify key logistical aims, analyse available quantitative models and point out modelling challenges in SFLM, is investigated in Chapter 2. In this chapter, key logistical aims in LM, FLM and SFLM phases are identified, and available quantitative models are analysed to point out modelling challenges in SFLM. A literature review on quantitative studies is conducted and also qualitative studies are consulted to better understand the key logistical aims and to identify the relevant system scope issues. The main findings of the literature review indicate that (i) most studies rely on a completely deterministic environment, (ii) the food waste challenge in logistics has not received sufficient attention, (iii) traveled distance is often used as a single indicator to estimate related transportation cost and emissions, and (iv) most studies propose single objective models for the food logistics problems. This chapter concludes that new and advanced quantitative models are needed that take specific SFLM requirements from practice into consideration to support business decisions and capture food supply chain dynamics. These findings motivated us to work on the following research objectives RO2, RO3, RO4 and RO5. RO2, which is to analyse the relationship between economic (cost) and environmental (transportation carbon emissions) performance in a network problem of a perishable product, is investigated in Chapter 3. This chapter presents a multi-objective linear programming (MOLP) model for a generic beef logistics network problem. The objectives of the model are (i) minimizing total logistics cost and (ii) minimizing total amount of greenhouse gas emissions from transportation operations. The model is solved using the e-constraint method. This study breaks away from the literature on logistics network models by simultaneously considering transportation emissions (affected by road structure, vehicle and fuel types, weight loads of vehicles, traveled distances), return hauls and product perishability in a MOLP model. We present computational results and analyses based on the application of the model to a real-life international beef logistics chain operating in Nova Andradina, Mato Grosso do Sul, Brazil, and exporting beef to the European Union. Trade-off relationships between multiple objectives are observed by the derived Pareto frontier that presents the cost of being sustainable from the point of reducing transportation emissions. The results indicate the importance of distances between actors in terms of environmental impact. Moreover, sensitivity analysis on important practical parameters show that export ports' capacities put pressure on the logistics system; decreasing fuel efficiency due to the bad infrastructure has negative effects on cost and emissions; and green tax incentives result in economic and environmental improvement. RO3, which is to investigate the performance implications of accommodating explicit transportation energy use and traffic congestion concerns in a two-echelon capacitated vehicle routing problem (2E-CVRP), is investigated in Chapter 4. The multi-echelon distribution strategy in which freight is delivered to customers via intermediate depots rather than using direct shipments is an increasingly popular strategy in urban logistics. Its popularity is primarily due to the fact that it alleviates the environmental (e.g., energy usage and congestion) and social (e.g., traffic-related air pollution, accidents and noise) consequences of logistics operations. This chapter presents a comprehensive mixed integer linear programming formulation for a time-dependent 2E-CVRP that accounts for vehicle type, traveled distance, vehicle speed, load, multiple time zones and emissions. A case study in a supermarket chain operating in the Netherlands shows the applicability of the model to a real-life problem. Several versions of the model, each differing with respect to the objective function, are tested to produce a number of selected Key Performance Indicators (KPIs) relevant to distance, time, fuel consumption and cost. This chapter offers insight in the economies of environmentally-friendly vehicle routing in two-echelon distribution systems. The results suggest that an environmentally-friendly solution is obtained from the use of a two-echelon distribution system, whereas a single-echelon distribution system provides the least-cost solution. RO4, which is to investigate the performance implications of accommodating explicit transportation energy use, product waste and demand uncertainty concerns in an inventory routing problem (IRP), is investigated in Chapter 5. Traditional assumptions of constant distribution costs between nodes, unlimited product shelf life and deterministic demand used in the IRP literature restrict the usefulness of the proposed models in current food logistics systems. From this point of view, our interest in this chapter is to enhance the traditional models for the IRP to make them more useful for decision makers in food logistics management. Therefore, we present a multi-period IRP model that includes truck load dependent (and thus route dependent) distribution costs for a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand. A case study on the fresh tomato distribution operations of a supermarket chain shows the applicability of the model to a real-life problem. Several variations of the model, each differing with respect to the considered aspects, are employed to present the benefits of including perishability and explicit fuel consumption concerns in the model. The results suggest that the proposed integrated model can achieve significant savings in total cost while satisfying the service level requirements, and thus offers better support to decision makers. RO5, which is to analyse the benefits of horizontal collaboration in a green IRP for perishable products with demand uncertainty, is investigated in Chapter 6. This chapter presents a decision support model, which includes a comprehensive evaluation of CO2 emission and fuel consumption, perishability, and a service level constraint for meeting uncertain demand, for the IRP with multiple suppliers and customers. The model allows to analyse the benefits of horizontal collaboration in the IRP with respect to several KPIs, i.e., total emissions, total driving time, total routing cost comprised of fuel and wage cost, total inventory cost, total waste cost, and total cost. A case study on the distribution operations of two suppliers, where the first supplier produces figs and the second supplier produces cherries, shows the applicability of the model to a real-life problem. The results show that horizontal collaboration among the suppliers contributes to the decrease of aggregated total cost and emissions in the logistics system, whereas the obtained gains are sensitive to the changes in parameters such as supplier size or maximum product shelf life. According to the experiments, the aggregated total cost benefit from cooperation varies in a range of about 4-24% and the aggregated total emission benefit varies in a range of about 8-33%. Integrated findings from Chapters 2, 3, 4, 5 and 6 contribute to the SFLM literature by (i) reflecting the state of the art on the topic of quantitative logistic models which have sustainability considerations, (ii) providing decision support models which can be used by decision makers to improve the performance of the sustainable food logistics systems in terms of logistics cost, transportation energy use and carbon emissions, and/or product waste, and (iii) presenting the applicability of the proposed models in different case studies based on mainly real data, multiple scenarios, and analysis. The developed decision support models exploit several logistics improvement opportunities regarding transportation energy use and emissions, and/or product waste to better aid SFLM, as distinct from their counterparts in literature. To conclude, the case study implementations in this thesis demonstrate that (i) perishability and explicit consideration of fuel consumption are important aspects in logistics problems, and (ii) the provided decision support models can be used in practice by decision makers to further improve sustainability performance of the food logistics systems. </p

Green supply chain quantitative models for sustainable inventory management: A review

[EN] This paper provides a systematic and up-to-date review and classification of 91 studies on quantitative methods of green supply chains for sustainable inventory management. It particularly identifies the main study areas, findings and quantitative models by setting a point for future research opportunities in sustainable inventory management. It seeks to review the quantitative methods that can better contribute to deal with the environmental impact challenge. More specifically, it focuses on different supply chain designs (green supply chain, sustainable supply chain, reverse logistics, closed-loop supply chain) in a broader application context. It also identifies the most important variables and parameters in inventory modelling from a sustainable perspective. The paper also includes a comparative analysis of the different mathematical programming, simulation and statistical models, and their solution approach, with exact methods, simulation, heuristic or meta-heuristic solution algorithms, the last of which indicate the increasing attention paid by researchers in recent years. The main findings recognise mixed integer linear programming models supported by heuristic and metaheuristic algorithms as the most widely used modelling approach. Minimisation of costs and greenhouse gas emissions are the main objectives of the reviewed approaches, while social aspects are hardly addressed. The main contemplated inventory management parameters are holding costs, quantity to order, safety stock and backorders. Demand is the most frequently shared information. Finally, tactical decisions, as opposed to strategical and operational decisions, are the main ones.The research leading to these results received funding from the Grant RTI2018-101344-B-I00 funded by MCIN/AEI/10.13039/501100011033 and by "ERDF A way of making Europe". It was also funded by the National Agency for Research and Development (ANID) / Scholarship Program/Doctorado Becas en el Extranjero/2020 72210174.Becerra, P.; Mula, J.; Sanchis, R. (2021). Green supply chain quantitative models for sustainable inventory management: A review. Journal of Cleaner Production. 328:1-16. https://doi.org/10.1016/j.jclepro.2021.129544S11632

Applications of the Internet of Things and optimization to inventory and distribution management

This thesis is part of the IoFEED (EU funded) project, which aims to monitor approximately 325 farm bins and investigates business processes carried out between farmers and animal feed producers. We propose a computer-aided system to control and optimize the supply chain to deliver animal feed to livestock farms. Orders can be of multiple types of feed, shipped from multiple depots using a fleet of heterogeneous vehicles with multiple compartments. Additionally, this case considers some business-specific constraints, such as product compatibility, facility accessibility restrictions, prioritized locations, or bio-security constraints. A digital twin based approach is implemented at the farm level by installing sensors to remotely measure the inventories. This thesis also embraces these sensors' design and manufacturing process, seeking the required precision and easy deployability at scale. Our approach combines biased-randomization techniques with a simheuristic framework to make use of data provided by the sensors. The analysis of results is based on these two real pilots, and showcases the insights obtained during the IoFEED project. The results of this thesis show how the Internet of Things and simulation-based optimization methods combine successfully to optimize deliveries of feed to livestock farms.Esta tesis forma parte del proyecto IoFeeD, financiado por la Unión Europea, que tiene como objetivo monitorizar remotamente el stock de 325 contenedores agrícolas e investigar los procesos comerciales llevados a cabo entre agricultores y productores de pienso. Proponemos un sistema de ayuda a la toma de decisiones para controlar y optimizar la cadena de suministro de pienso en las explotaciones ganaderas. Los pedidos pueden ser de varios tipos de pienso y pueden enviarse desde varios centros de fabricación mediante el uso de una flota de vehículos heterogéneos con varios compartimentos. Además, se tienen en cuenta algunas restricciones específicas de la empresa, como, por ejemplo, la compatibilidad del producto, las restricciones de accesibilidad en las instalaciones, las ubicaciones priorizadas o las restricciones de bioseguridad. A escala de granja, se implementa un enfoque basado en gemelos digitales mediante la instalación de sensores para medir los inventarios de forma remota. En el marco de esta tesis, se desarrollan estos sensores buscando la precisión requerida, así como las características oportunas que permitan su instalación a gran escala. Nuestro enfoque combina técnicas de aleatorización sesgada con un marco simheurístico para hacer uso de los datos proporcionados por los sensores. El análisis de los resultados se basa en estos dos pilotos reales y muestra las ideas obtenidas durante el proyecto IoFeeD. Los resultados de esta tesis muestran cómo la internet de las cosas y los métodos de optimización basados en simulación se combinan con éxito para optimizar las operaciones de suministro de pienso para el consumo animal en las explotaciones ganaderas.Aquesta tesi forma part del projecte IoFeeD, finançat per la Unió Europea, que té com a objectiu controlar remotament l'estoc de 325 sitges i investigar els processos de negoci duts a terme entre agricultors i productors de pinso. Proposem un sistema d'ajuda a la presa de decisions per controlar i optimitzar la cadena de subministrament de pinso a les explotacions ramaderes. Les comandes poden ser de diversos tipus de pinso i es poden enviar des de diversos centres de fabricació mitjançant l'ús d'una flota de vehicles heterogenis amb diversos compartiments. A més, es tenen en compte algunes restriccions específiques de l'empresa, com ara la compatibilitat del producte, les restriccions d'accessibilitat a les instal·lacions, les ubicacions prioritzades o les restriccions de bioseguretat. A escala de granja, s'implementa un enfocament basat en bessons digitals mitjançant la instal·lació de sensors per mesurar remotament els inventaris. En el marc de la tesi, es desenvolupa aquest sensor cercant la precisió requerida i les característiques oportunes que en permetin la instal·lació a gran escala. El nostre enfocament combina tècniques d'aleatorització esbiaixada amb un marc simheurístic per fer ús de les dades proporcionades pels sensors. L'anàlisi dels resultats es basa en aquests dos pilots reals i mostra les idees obtingudes durant el projecte IoFeeD. Els resultats d'aquesta tesi mostren com la internet de les coses i els mètodes d'optimització basats en simulació es combinen amb èxit per optimitzar les operacions de subministrament de pinso per al consum animal a les explotacions ramaderes.Tecnologies de la informació i de xarxe

Integrated Inventory Routing Problem with Quality Time Windows and Loading Cost for Deteriorating Items under Discrete Time

We investigate an integrated inventory routing problem (IRP) in which one supplier with limited production capacity distributes a single item to a set of retailers using homogeneous vehicles. In the objective function we consider a loading cost which is often neglected in previous research. Considering the deterioration in the products, we set a soft time window during the transportation stage and a hard time window during the sales stage, and to prevent jams and waiting cost, the time interval of two successive vehicles returning to the supplier’s facilities is required not to be overly short. Combining all of these factors, a two-echelon supply chain mixed integer programming model under discrete time is proposed, and a two-phase algorithm is developed. The first phase uses tabu search to obtain the retailers’ ordering matrix. The second phase is to generate production scheduling and distribution routing, adopting a saving algorithm and a neighbourhood search, respectively. Computational experiments are conducted to illustrate the effectiveness of the proposed model and algorithm