scholarly journals Optimization of Hybrid Hub-and-Spoke Network Operation for Less-Than-Truckload Freight Transportation considering Incremental Quantity Discount

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Weiya Chen ◽  
Kaixian He ◽  
Xiaoping Fang
Keyword(s):  
Programming Model ◽  
Load Capacity ◽  
Freight Transportation ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Road Transportation ◽  
Quantity Discount ◽  
Hub And Spoke ◽  
Network Operation ◽  
Truck Load

This paper presents a mixed integer linear programming model (MILP) for optimizing the hybrid hub-and-spoke network operation for a less-than-truckload transportation service. The model aims to minimize the total operation costs (transportation cost and transfer cost), given the determined demand matrix, truck load capacity, and uncapacitated road transportation. The model also incorporates an incremental quantity discount function to solve the reversal of the total cost and the total demand. The model is applied to a real case of a Chinese transportation company engaged in nationwide freight transportation. The numerical example shows that, with uncapacitated road transportation, the total costs and the total vehicle trips of the hybrid hub-and-spoke network operation are, respectively, 8.0% and 15.3% less than those of the pure hub-and-spoke network operation, and the assumed capacity constraints in an extension model result in more target costs on the hybrid hub-and-spoke network. The two models can be used to support the decision making in network operations by transportation and logistics companies.

scholarly journals Hierarchical hub location model and hybrid algorithm for integration of urban and rural public transport

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877326 ◽  
Author(s):  
Wei Zhong ◽  
Zhicai Juan ◽  
Fang Zong ◽  
Huishuang Su
Keyword(s):  
Public Transport ◽  
Rural Areas ◽  
Programming Model ◽  
Transportation Network ◽  
Transportation Cost ◽  
Capacity Constraint ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub And Spoke ◽  
Total Cost

Integration of urban and rural infrastructure is critical to integrating urban and rural public transport. A public transport hub is an important element of infrastructure, and it is the key facilities that serve as transferring points between cities and towns. The location of hub is related to the convenience of travel for urban and rural residents and the closeness of economic interactions between urban and rural areas. In this article, considering the background of the integration of urban and rural public transport, from the perspective of public transport hubs in urban and central town, a multi-level hub-and-spoke network is designed, and the location of integration of urban and rural public transport hub is determined. Based on the connection associated with central towns and the capacity constraints of hubs and to achieve the minimum total cost, this article proposes a mixed-integer programming model that employs a genetic and tabu search hybrid optimization algorithm to validate and analyze, which used the urban and rural public transport data from a specified area of Shandong province in China. The results indicate that the model can simultaneously determine locations for hubs in cities and central towns while minimizing total cost. The hub capacity constraint significantly influences the location of two-level hubs. The hub capacity constraint in the model can reduce the transportation cost for an entire network and optimize the transportation network. This study on urban and rural public transport hub location in a hub-and-spoke network not only reduces the transportation cost of the network but also completes and supplements the location theory of integration of urban and rural public transport.

Insights to optimise marketing decisions on pig-grower farms

2019 ◽  
Vol 59 (6) ◽  
pp. 1126 ◽  
Author(s):  
S. V. Rodríguez-Sanchez ◽  
L. M. Pla-Aragones ◽  
R. De Castro
Keyword(s):  
Weight Control ◽  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Management Policy ◽  
Mixed Integer ◽  
Factors Affecting ◽  
Pig Production ◽  
Marketing Policy ◽  
Feeding Program

Modern pig production in a vertically integrated company is a highly specialised and industrialised activity, requiring increasingly complex and critical decision-making. The present paper focuses on the decisions made on the pig-grower farms operating on an all-in–all-out management policy at the last stage of pig production. Based on a mixed-integer linear-programming model, an assessment for specific parameters to support marketing decisions on farms without individual weight control is made. The analysis of several key factors affecting the optimal marketing policy, such as transportation cost, when and how many pigs to deliver to the abattoir and weight homogeneity of the batch, served to gain insight into marketing decisions. The results confirmed that not just the feeding program, but also the grading price system, transportation and batch homogeneity have an enormous impact on the optimal marketing policy of fattening farms in a vertically integrated company. In addition, within the range of conditions considered, a time window of 4 weeks was deemed as optimal for delivering animals to the abattoir and the subsequent revenue was 15% higher than with traditional marketing rules.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

scholarly journals Bi-objective load balancing multiple allocation hub location: a compromise programming approach

2020 ◽  
Vol 296 (1-2) ◽  
pp. 363-406 ◽  
Author(s):  
Rahimeh Neamatian Monemi ◽  
Shahin Gelareh ◽  
Anass Nagih ◽  
Dylan Jones
Keyword(s):  
Spatial Distribution ◽  
Transportation Cost ◽  
Compromise Programming ◽  
Mixed Integer ◽  
Programming Approach ◽  
Hub Location ◽  
Hub And Spoke ◽  
Classical Models ◽  
Linear Programming Formulation ◽  
Multiple Allocation

AbstractIn this paper we address unbalanced spatial distribution of hub-level flows in an optimal hub-and-spoke network structure of median-type models. Our study is based on a rather general variant of the multiple allocation hub location problems with fixed setup costs for hub nodes and hub edges in both capacitated and uncapacitated variants wherein the number of hub nodes traversed along origin-destination pairs is not constrained to one or two as in the classical models.. From the perspective of an infrastructure owner, we want to make sure that there exists a choice of design for the hub-level sub-network (hubs and hub edges) that considers both objectives of minimizing cost of transportation and balancing spatial distribution of flow across the hub-level network. We propose a bi-objective (transportation cost and hub-level flow variance) mixed integer non-linear programming formulation and handle the bi-objective model via a compromise programming framework. We exploit the structure of the problem and propose a second-order conic reformulation of the model along with a very efficient matheuristics algorithm for larger size instances.

scholarly journals A Multimodal Passenger-and-Package Sharing Network for Urban Logistics

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yuxiong Ji ◽  
Yujing Zheng ◽  
Jizhou Zhao ◽  
Yu Shen ◽  
Yuchuan Du
Keyword(s):  
Network Performance ◽  
Programming Model ◽  
Mixed Integer ◽  
Covering Problem ◽  
Hub Location ◽  
Real World Data ◽  
Hub And Spoke ◽  
Taxi Drivers ◽  
Optimal Value ◽  
Peripheral Areas

This paper envisions a multimodal passenger-and-package sharing (PPS) network for urban logistics integrating metro, taxi, and truck. A hub-and-spoke structure is designed including hubs located at metro stations and service stores connected to the hubs. Packages are transported by metro on backbone links between the hubs and are carried by taxis or trucks between service stores and hubs, depending on the unit costs of these two modes and capacity constraint of the taxi. A mixed integer linear programming model for hub location problems—fusing the multiassignment p-hub median problem without capacity constraints and the capacitated multiassignment p-hub covering problem—is formulated to optimize the multimodal PPS network. The model is implemented based on the real-world data in Shanghai (China) under a series of scenarios to evaluate the network performance from two perspectives: the number of hubs and the proportion of taxi drivers who are willing to carry packages. The scenarios show that with increased number of hubs, the spatial distribution of hubs disperses from the city center to peripheral areas and more areas can be serviced by taxis. There is, however, a trade-off between the operation cost saved by taxis and the establishment cost of an extra hub. The analysis also presents that if the proportion of taxis willing to carry packages associates with the incentive payments to taxi drivers, an optimal value of incentives exists, by balancing the operation costs of taxis and trucks.

Network Design for Shipping Service of Large-Scale Intermodal Liners

2012 ◽  
Vol 2269 (1) ◽  
pp. 42-50 ◽  
Author(s):  
Qiang Meng ◽  
Shuaian Wang ◽  
Zhiyuan Liu
Keyword(s):  
Network Design ◽  
Large Scale ◽  
Programming Model ◽  
Transportation Network ◽  
Liner Shipping ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Hub And Spoke ◽  
Shipping Company ◽  
Proposed Model

A model was developed for network design of a shipping service for large-scale intermodal liners that captured essential practical issues, including consistency with current services, slot purchasing, inland and maritime transportation, multiple-type containers, and origin-to-destination transit time. The model used a liner shipping hub-and-spoke network to facilitate laden container routing from one port to another. Laden container routing in the inland transportation network was combined with the maritime network by defining a set of candidate export and import ports. Empty container flow is described on the basis of path flow and leg flow in the inland and maritime networks, respectively. The problem of network design for shipping service of an intermodal liner was formulated as a mixed-integer linear programming model. The proposed model was used to design the shipping services for a global liner shipping company.

scholarly journals Five-Echelon Multiobjective Health Services Supply Chain Modeling under Disruption

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Farnaz Javadi Gargari ◽  
Mahjoube Sayad ◽  
Seyed Ali Posht Mashhadi ◽  
Abdolhossein Sadrnia ◽  
Arman Nedjati ◽  
...  
Keyword(s):  
Supply Chain ◽  
Optimization Model ◽  
Optimization Problem ◽  
Programming Model ◽  
Transportation Cost ◽  
Real Data ◽  
Mixed Integer ◽  
Fixed Cost ◽  
Hub Location ◽  
Goal Programming Model

Medicine unreliability problem is taken into consideration as one of the most important issues in health supply chain management. This research is associated with the development of a multiobjective optimization problem for the selection of suppliers and distributors. To achieve the purposes, the optimal quota allocation is determined with respect to disruption of suppliers in a five-echelon supply chain network and consideration of the distributor centers as a hub location-allocation mode. The objective of the optimization model is involved in simultaneous minimization of transactions costs dealing with suppliers, expected purchasing costs from suppliers, expected percentages of delayed and returned products in each distributor, as well as transportation cost in each echelon and fixed cost for distributor centers, and finally maximization of the expected scores for suppliers and high priority of product customers. The optimization problem is formulated as a mixed-integer nonlinear programming model. The proposed optimization model is utilized to investigate a numerical case study for asthma-specific medicines. The analyzing procedure is conducted based on the collected real data from Cobel Darou pharmaceutical company in 2019. Furthermore, a fuzzy multichoice goal programming model is considered to solve the proposed optimization model by R optimization solver. The numerical results confirmed the authenticity of the model.

scholarly journals A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jin Qin ◽  
Hui Xiang ◽  
Yong Ye ◽  
Linglin Ni
Keyword(s):  
Simulated Annealing ◽  
Facility Location ◽  
Programming Model ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Optimal Decision ◽  
Location Decision ◽  
Inventory Cost ◽  
Stochastic Demands ◽  
Capacitated Facility Location

A stochastic multiproduct capacitated facility location problem involving a single supplier and multiple customers is investigated. Due to the stochastic demands, a reasonable amount of safety stock must be kept in the facilities to achieve suitable service levels, which results in increased inventory cost. Based on the assumption of normal distributed for all the stochastic demands, a nonlinear mixed-integer programming model is proposed, whose objective is to minimize the total cost, including transportation cost, inventory cost, operation cost, and setup cost. A combined simulated annealing (CSA) algorithm is presented to solve the model, in which the outer layer subalgorithm optimizes the facility location decision and the inner layer subalgorithm optimizes the demand allocation based on the determined facility location decision. The results obtained with this approach shown that the CSA is a robust and practical approach for solving a multiple product problem, which generates the suboptimal facility location decision and inventory policies. Meanwhile, we also found that the transportation cost and the demand deviation have the strongest influence on the optimal decision compared to the others.

scholarly journals Single Item Supplier Selection and Order Allocation Problem with a Quantity Discount and Transportation Costs

2020 ◽  
Vol 12 (1) ◽  
pp. 20-38
Author(s):  
Getachew Basa ◽  
Till Becker ◽  
Abdelkader Kedir
Keyword(s):  
Supplier Selection ◽  
Lot Sizing ◽  
Transportation Cost ◽  
Transportation Costs ◽  
Mixed Integer ◽  
Nonlinear Program ◽  
Order Allocation ◽  
Quantity Discount ◽  
Numerical Illustration ◽  
Single Item

In this paper, we address a single item supplier selection, economic lot-sizing, and order assignment problem under quantity discount environment and transportation costs. A mixed-integer nonlinear program (MINP) model is developed with minimization of cost as its objective, while lead-time, the capacity of the supplier and demand of the product are incorporated as constraints. The total cost considered includes annual inventory holding cost, ordering cost, transportation cost and purchase cost. An efficient and effective genetic algorithm (GA) with problem-specific operators is developed and used to solve the proposed MINP model.  The  model is illustrated through a numerical example and the results show that the GA can solve the model in less than a minute. Moreover, the results of the numerical illustration show that the item cost and transportation cost are the deciding factors in selecting suppliers and allocating orders. Keywords: Supplier selection, Economic Order Quantity, Order allocation, Mixed-integer nonlinear programming.

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