755,547 research outputs found
A study on the benefits of integrating inventory and routing decisions in a city logistics context
No full textThis study investigates the potential of utilizing an Urban Consolidation Center (UCC) or a city hub as an intermediate storage facility within a B2B two-echelon urban distribution system. The main objective is to assess the advantages of integrating inventory and routing decisions in contrast to a traditional approach where the city hub functions only as a consolidation point. Two scenarios are explored in this study: a traditional one involving sequential inventory and routing decisions, and an integrated one where these decisions are made simultaneously.
A traditional problem in which inventory and routing decisions are taken sequentially is solved using the same model and method as in [1]. In the sequential scenario, various replenishment methods are employed for the inventory aspect, and a Large Neighbourhood Search (LNS) metaheuristic is utilized to optimize routing decisions from the UCC to the retailers. The integrated scenario is addressed using a matheuristic algorithm that combines mathematical optimization techniques with heuristics. A matheuristic algorithm based on the one presented in [2] is proposed to solve the integrated problem. We adapt the method to our specific problem context by extending it to a multi-product, heterogeneous, multi-trip context with a more complex objective function that also includes holding costs, order costs, and duration-based routing costs.
Computational results consistently demonstrate the superiority of the integrated approach across multiple performance metrics, including costs, logistics ratio, number of urban trips, loading degree, and distance traveled. A sensitivity analysis highlights critical factors, including retailer storage capacity, order cost, and retailer participation, that influence the implementation of the integrated scenario. Retailers can benefit from the implementation of the integrated scenario to reduce their storage capacity requirements and allocate the available space for other purposes. Additionally, a higher order cost reduces the savings obtained from implementing the integrated scenario. Furthermore, higher levels of retailer participation result in more substantial cost reductions in both the second and first echelons.
Further analysis is conducted to investigate the impact of different transshipment costs on the cost difference between the sequential and integrated scenarios. As transshipment costs increase, the cost difference between the integrated and sequential scenarios becomes even larger.
References
[1] Iswari, T., Braekers, K., and Caris, A., (2023). Analyzing the benefits of a city hub: an inventory and routing perspective. Computers & Industrial Engineering, Vol 185, 109629.
[2] Bertazzi, L., Coelho, L.C., De Maio, A. and Laganà, D. (2019). A matheuristic algorithm for the multi-depot inventory routing problem. Transportation Research Part E: Logistics and Transportation Review, 122:524–544
A study on the benefits of integrating inventory and routing decisions in a city logistics context
No full textThis study investigates the potential of utilizing an Urban Consolidation Center (UCC) or a city hub as an intermediate storage facility within a B2B two-echelon urban distribution system. The main objective is to assess the advantages of integrating inventory and routing decisions in contrast to a traditional approach where the city hub functions only as a consolidation point. Two scenarios are explored in this study: a traditional one involving sequential inventory and routing decisions, and an integrated one where these decisions are made simultaneously.
A traditional problem in which inventory and routing decisions are taken sequentially is solved using the same model and method as in [1]. In the sequential scenario, various replenishment methods are employed for the inventory aspect, and a Large Neighbourhood Search (LNS) metaheuristic is utilized to optimize routing decisions from the UCC to the retailers. The integrated scenario is addressed using a matheuristic algorithm that combines mathematical optimization techniques with heuristics. A matheuristic algorithm based on the one presented in [2] is proposed to solve the integrated problem. We adapt the method to our specific problem context by extending it to a multi-product, heterogeneous, multi-trip context with a more complex objective function that also includes holding costs, order costs, and duration-based routing costs.
Computational results consistently demonstrate the superiority of the integrated approach across multiple performance metrics, including costs, logistics ratio, number of urban trips, loading degree, and distance traveled. A sensitivity analysis highlights critical factors, including retailer storage capacity, order cost, and retailer participation, that influence the implementation of the integrated scenario. Retailers can benefit from the implementation of the integrated scenario to reduce their storage capacity requirements and allocate the available space for other purposes. Additionally, a higher order cost reduces the savings obtained from implementing the integrated scenario. Furthermore, higher levels of retailer participation result in more substantial cost reductions in both the second and first echelons.
Further analysis is conducted to investigate the impact of different transshipment costs on the cost difference between the sequential and integrated scenarios. As transshipment costs increase, the cost difference between the integrated and sequential scenarios becomes even larger.
References
[1] Iswari, T., Braekers, K., and Caris, A., (2023). Analyzing the benefits of a city hub: an inventory and routing perspective. Computers & Industrial Engineering, Vol 185, 109629.
[2] Bertazzi, L., Coelho, L.C., De Maio, A. and Laganà, D. (2019). A matheuristic algorithm for the multi-depot inventory routing problem. Transportation Research Part E: Logistics and Transportation Review, 122:524–544
Optimizing City Logistics: Analyzing the Benefits of a City Hub by means of Integrated Inventory Routing Decisions
No full textAlthough extensive literature exists on the use of urban consolidation centers (UCC) as a solution for
urban logistics, its implementation is often not well supported by operational and tactical planning
tools. Moreover, it is likely that the efficiency and sustainability of modern urban supply chains can
be considerably improved by coordination and collaboration among supply chain actors. The sharing
of logistic resources such as transport vehicles and urban logistics space is key to reduce costs. Even
though the city is often not the main decision maker in new logistics initiatives, it can both support
the supply chain companies operating on its territory and nudge them in a sustainable direction.
Many cities struggle, however, to develop appropriate policies for the supply chain services in their
urban region.
In our research we investigate how to organize distribution activities for B2B flows in a multi-echelon
distribution system making use of a UCC. UCCs still offer new opportunities for urban B2B flows, as
they could act as an intermediate storage facility, allowing retailers to save costly storage space in
expensive commercial areas (Johansson and Björklund (2017). Only a few research efforts have
studied the integration of inventory management (i.e., store replenishment) and distribution (i.e.,
routing) decisions in such a system (e.g., De Maio and Laganà (2020)). While there is a large body of
literature on related inventory routing problems (IRPs), most of this work does not account for the
specific aspects that arise in urban areas (Archetti and Bertazzi, 2021).
Our goal is to analyze to what extent the integration of inventory and routing decisions leads to
additional operational benefits compared to a traditional setting in which the UCC is only used as a
consolidation point. To address our research question, two scenarios are considered and compared:
a traditional one in which inventory and routing decisions are taken sequentially (as in Iswari et al.,
2023) and an integrated one in which both decisions are taken simultaneously. In this second
scenario, the city hub simultaneously determines if and how many products of each type will be
delivered to the retailers every day, and the corresponding delivery routes, while ensuring sufficient
inventory at the retailers. This results in a multi-period Inventory Routing Problem (IRP) with multiple
products, time windows, a heterogeneous fleet and multiple trips.
A matheuristic algorithm is proposed to solve this integrated inventory routing problem. Our
algorithm is based on the same idea of Bertazzi et al. (2019), who first generate promising routes and
then solve a model to select both which routes to apply on which days and to define the
corresponding delivery quantities. However, as our problem is considerably different from the one of
Bertazzi et al. (2019), several changes are made. First, in our problem setting all products originate
from a single location, i.e. the city hub, thus we only consider the second and third phases of the
method of Bertazzi et al. (2019). As such, our two phase matheuristic algorithm consists of a route
generation phase and an optimization phase. Second, as we do not create customer clusters, the
route generation phase is based on solving a VRP rather than a TSP per cluster. Third, we adapt the
method to our specific problem context by extending it to a multi-product, heterogeneous, multi-trip
context with a more complex objective function that also includes holding costs, order costs, and
duration-based routing costs. Due to the increased complexity, we propose an algorithm variant in
which we solve the MILP model in the optimization phase heuristically using column generation.
An experimental setup is designed to provide insights into critical factors that impact the
implementation of the integrated inventory routing scenario. Retailer storage capacity is found to
significantly influence the cost savings achieved through integration. Although the integrated
scenario consistently yields lower costs, the potential savings of the integrated scenario decrease as
the storage capacity at retailers decreases, as there are fewer opportunities for consolidating
deliveries and achieving efficiency gains. Additionally, the order cost plays a crucial role in shaping
the cost savings obtained from this scenario. A higher order cost leads to reduced savings.
Furthermore, retailer participation in the integrated decision-making process is a critical determinant
of cost savings. Higher levels of retailer participation result in more substantial cost reductions in
both the second and first echelons. Actively involving retailers in the decision-making process allows
for better resource utilization and overall cost benefits. Finally, as the cost of organizing a city hub
may considerably offset potential savings, a sensitivity analysis of transshipment costs is also
performed. The results indicate that in specific settings, such as a high number of retailers, using the
city hub may result in minimal or no cost savings, particularly in case of high transshipment costs.
Additionally, the findings highlight that the integrated inventory routing scenario consistently
outperforms the scenario in which separate inventory and routing decisions are taken. Lower costs
per delivery point are observed across all transshipment cost ranges considered in both scenarios. As
transshipment costs increase, the cost difference becomes even larger.This study is supported by the Special Research Fund (BOF) of Hasselt University, Belgium
(BOF20OWB26) and by VLAIO cSBO project STRAUSSHBC.2023.0008. The computational resources
and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by
the Research Foundation Flanders (FWO) and the Flemish Government
Optimizing City Logistics: Analyzing the Benefits of a City Hub by means of Integrated Inventory Routing Decisions
No full textAlthough extensive literature exists on the use of urban consolidation centers (UCC) as a solution for
urban logistics, its implementation is often not well supported by operational and tactical planning
tools. Moreover, it is likely that the efficiency and sustainability of modern urban supply chains can
be considerably improved by coordination and collaboration among supply chain actors. The sharing
of logistic resources such as transport vehicles and urban logistics space is key to reduce costs. Even
though the city is often not the main decision maker in new logistics initiatives, it can both support
the supply chain companies operating on its territory and nudge them in a sustainable direction.
Many cities struggle, however, to develop appropriate policies for the supply chain services in their
urban region.
In our research we investigate how to organize distribution activities for B2B flows in a multi-echelon
distribution system making use of a UCC. UCCs still offer new opportunities for urban B2B flows, as
they could act as an intermediate storage facility, allowing retailers to save costly storage space in
expensive commercial areas (Johansson and Björklund (2017). Only a few research efforts have
studied the integration of inventory management (i.e., store replenishment) and distribution (i.e.,
routing) decisions in such a system (e.g., De Maio and Laganà (2020)). While there is a large body of
literature on related inventory routing problems (IRPs), most of this work does not account for the
specific aspects that arise in urban areas (Archetti and Bertazzi, 2021).
Our goal is to analyze to what extent the integration of inventory and routing decisions leads to
additional operational benefits compared to a traditional setting in which the UCC is only used as a
consolidation point. To address our research question, two scenarios are considered and compared:
a traditional one in which inventory and routing decisions are taken sequentially (as in Iswari et al.,
2023) and an integrated one in which both decisions are taken simultaneously. In this second
scenario, the city hub simultaneously determines if and how many products of each type will be
delivered to the retailers every day, and the corresponding delivery routes, while ensuring sufficient
inventory at the retailers. This results in a multi-period Inventory Routing Problem (IRP) with multiple
products, time windows, a heterogeneous fleet and multiple trips.
A matheuristic algorithm is proposed to solve this integrated inventory routing problem. Our
algorithm is based on the same idea of Bertazzi et al. (2019), who first generate promising routes and
then solve a model to select both which routes to apply on which days and to define the
corresponding delivery quantities. However, as our problem is considerably different from the one of
Bertazzi et al. (2019), several changes are made. First, in our problem setting all products originate
from a single location, i.e. the city hub, thus we only consider the second and third phases of the
method of Bertazzi et al. (2019). As such, our two phase matheuristic algorithm consists of a route
generation phase and an optimization phase. Second, as we do not create customer clusters, the
route generation phase is based on solving a VRP rather than a TSP per cluster. Third, we adapt the
method to our specific problem context by extending it to a multi-product, heterogeneous, multi-trip
context with a more complex objective function that also includes holding costs, order costs, and
duration-based routing costs. Due to the increased complexity, we propose an algorithm variant in
which we solve the MILP model in the optimization phase heuristically using column generation.
An experimental setup is designed to provide insights into critical factors that impact the
implementation of the integrated inventory routing scenario. Retailer storage capacity is found to
significantly influence the cost savings achieved through integration. Although the integrated
scenario consistently yields lower costs, the potential savings of the integrated scenario decrease as
the storage capacity at retailers decreases, as there are fewer opportunities for consolidating
deliveries and achieving efficiency gains. Additionally, the order cost plays a crucial role in shaping
the cost savings obtained from this scenario. A higher order cost leads to reduced savings.
Furthermore, retailer participation in the integrated decision-making process is a critical determinant
of cost savings. Higher levels of retailer participation result in more substantial cost reductions in
both the second and first echelons. Actively involving retailers in the decision-making process allows
for better resource utilization and overall cost benefits. Finally, as the cost of organizing a city hub
may considerably offset potential savings, a sensitivity analysis of transshipment costs is also
performed. The results indicate that in specific settings, such as a high number of retailers, using the
city hub may result in minimal or no cost savings, particularly in case of high transshipment costs.
Additionally, the findings highlight that the integrated inventory routing scenario consistently
outperforms the scenario in which separate inventory and routing decisions are taken. Lower costs
per delivery point are observed across all transshipment cost ranges considered in both scenarios. As
transshipment costs increase, the cost difference becomes even larger.This study is supported by the Special Research Fund (BOF) of Hasselt University, Belgium
(BOF20OWB26) and by VLAIO cSBO project STRAUSSHBC.2023.0008. The computational resources
and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by
the Research Foundation Flanders (FWO) and the Flemish Government
Analyzing the benefits of a city hub: An inventory and routing perspective
No full textCollaboration is one of the crucial elements in city logistics and it is often pursued by the introduction of two or multi-echelon systems using one or more intermediate consolidation points, such as Urban Consolidation Centers (UCCs), city depots, city hubs, etc. Our literature review shows that the study of inventory aspects in such a context is relatively unexplored. Therefore, this paper studies the effect of using a UCC or city hub in a B2B city logistics system in terms of both inventory and routing aspects. A multi-period optimization model is proposed to support the operational decisions in urban B2B distribution when using a city hub. We study the effect of introducing a city hub by comparing our model with a baseline model in which urban retailers operate without a city hub. The model accounts for the complexity of urban logistics by considering a heterogeneous vehicle fleet, the option to perform multiple trips per day, and strict customer time windows. A metaheuristic algorithm based on Large Neighborhood Search (LNS) is used to solve the route optimization problem for realistic problem instances. Extensive numerical experiments are conducted according to an experimental design and a statistical analysis. Results indicate that the introduction of a city hub leads to significant reductions in operational costs and societal impacts (e.g., loading degree, number of urban trips, traveled distances). Our analysis shows that these savings are significantly impacted by the problem context (e.g., replenishment policy, number of retailers, number of suppliers, and holding cost). For example, how retailers make replenishment decisions significantly impacts the costs of the overall system and the potential savings. The most cost-efficient replenishment method is often not the most interesting one from a societal perspective. Finally, from a city’s perspective, a sufficient number of retailers and suppliers should participate in the system to maximize consolidation opportunities. However, in relative terms, the largest potential savings by introducing a city hub are reached when not too many suppliers are included and suppliers have a relatively limited number of customers to serve.This study is supported by the Special Research Fund (BOF) of Hasselt University, Belgium with the BOF number: BOF20OWB26, the Research Foundation Flanders, Belgium (FWO junior research project G021422N), and by VLAIO cSBO project STRAUSS HBC.2023.0008. The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation Flanders (FWO) and the Flemish Government
Do You See What I See? A Simulation Analysis of Order Bundling within a Transparent User Network in Geographic Space
No full textThe Physical Internet (PI) concept presents a radical change with the aim to revert the unsustainable practices that are used for transporting goods. It identifies dedicated freight flows and transforms them into transparent open logistics networks which can be accessed by other users, such as shippers and carriers. In this paper, we test the universal network openness in which the users can tap into the PI network and place orders that will be assigned to the nearest available transport service and consequently delivered to the order sender. The objective of our paper is to investigate the impact of inserting extra service points into existing dedicated freight flows of a service-driven company. We simulate different transparency levels and routings to new pickup locations and evaluate the impact in terms of altered lead times, covered distances, and fill rates. The novel aspects presented herein are (1) deliveries based on decentralized location detection of the nearest order sender, (2) dynamically changing speed parameters of agents within specific geographic clusters based on their geo-locations in order to account for congestion levels, (3) more realistic routing strategies that consider the urban layout, and (4) transparent querying of nearest agents in space and time that meet specific conditions such as current ongoing processes, available capacity, and position. Finally, we identify the impact from a general/holistic perspective that emerges once extra orders are assigned to the service-driven company's fleet.Ambra, T (reprint author), Vrije Univ Brussel, Pleinlaan 2 PL 5-4-36, B-1050 Brussels, Belgium.
[email protected]
Concentration and Specialisation in a Full Truck Vehicle Routing Heuristic Algorithm
No full textPre- and end-haulage of intermodal container terminals involves the pickup or delivery of containers at customer
locations. The drayage of containers in the service area of an intermodal terminal has been modelled as a full truckload
pickup and delivery problem with time windows (FTPDPTW). The research investigates two concepts,
borrowed from geographical economics, in the context of the FTPDPTW: concentration and specialisation. The
concepts are translated into characteristics of time windows: more concentrated in the morning or in the afternoon; more
longer time windows than shorter ones in either morning or afternoon. Experiments are run for a number of instances to
investigate the effect of both concepts. It is shown that concentration leads to a higher number of routes and a
higher final cost
Concentration and Specialisation in a Full Truck Vehicle Routing Heuristic Algorithm
No full textPre- and end-haulage of intermodal container terminals involves the pickup or delivery of containers at customer
locations. The drayage of containers in the service area of an intermodal terminal has been modelled as a full truckload
pickup and delivery problem with time windows (FTPDPTW). The research investigates two concepts,
borrowed from geographical economics, in the context of the FTPDPTW: concentration and specialisation. The
concepts are translated into characteristics of time windows: more concentrated in the morning or in the afternoon; more
longer time windows than shorter ones in either morning or afternoon. Experiments are run for a number of instances to
investigate the effect of both concepts. It is shown that concentration leads to a higher number of routes and a
higher final cost
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