Collaborative transportation with overlapping coalitions

Guajardo, Mario; Rönnqvist, Mikael; Flisberg, Patrik; Frisk, Mikael

doi:10.1016/j.ejor.2018.05.001

Cited by 42 publications

(27 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Constraints (18) and (19) limit the arrival time of each vehicle for visiting customers served by vehicle sharing among DCs. Constraints (20) and (21) guarantee that each customer is served in their expected time windows. Constraints (22)- (26) are binary decision variables.…”

Section: Model Formulationmentioning

confidence: 99%

“…Population POP and the velocity of each particle are initialized, and the initial vehicle routes are generated according to the capacity constraints (8)-(9), subtour constraints (11)- (12), and time window constraints (16)- (21), and then the objective function values corresponding to each particle are found. The locations that replace the nondominated vectors are stored in the repository REP.…”

Section: Population Initializationmentioning

confidence: 99%

“…Neves-Moreira et al [ 20 ] developed a novel mathematical model for the freight transportation problem, which aimed to ensure resource synchronization among multiple nodes. Guajardo et al [ 21 ] proposed a mixed-integer linear programming model to minimize the total transportation costs in solving the collaborative alliance configuration problem. Chen et al [ 22 ] considered logistics resource sharing and presented a collaborative model based on the vehicle routing problem.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Collaborative multicenter logistics delivery network optimization with resource sharing

et al. 2020

View full text Add to dashboard Cite

Collaboration among logistics facilities in a multicenter logistics delivery network can significantly improve the utilization of logistics resources through resource sharing including logistics facilities, vehicles, and customer services. This study proposes and tests different resource sharing schemes to solve the optimization problem of a collaborative multicenter logistics delivery network based on resource sharing (CMCLDN-RS). The CMCLDN-RS problem aims to establish a collaborative mechanism of allocating logistics resources in a manner that improves the operational efficiency of a logistics network. A bi-objective optimization model is proposed with consideration of various resource sharing schemes in multiple service periods to minimize the total cost and number of vehicles. An adaptive grid particle swarm optimization (AGPSO) algorithm based on customer clustering is devised to solve the CMCLDN-RS problem and find Pareto optimal solutions. An effective elite iteration and selective endowment mechanism is designed for the algorithm to combine global and local search to improve search capabilities. The solution of CMCLDN-RS guarantees that cost savings are fairly allocated to the collaborative participants through a suitable profit allocation model. Compared with the computation performance of the existing nondominated sorting genetic algorithm-II and multi-objective evolutionary algorithm, AGPSO is more computationally efficient. An empirical case study in Chengdu, China suggests that the proposed collaborative mechanism with resource sharing can effectively reduce total operational costs and number of vehicles, thereby enhancing the operational efficiency of the logistics network.

show abstract

Section: Model Formulationmentioning

confidence: 99%

Section: Population Initializationmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Collaborative multicenter logistics delivery network optimization with resource sharing

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In recent years, the concept of collaboration has received increasing attention in production (e.g., Leng and Jiang 2018;Salamati-Hormozi et al 2018), logistics (e.g., Basso et al 2019;Guajardo et al 2018), and supply chain management (e.g., Herczeg et al 2018;Ponte et al 2018). In this context, collaboration is typically seen as a form of cooperation between two or more independent companies planning and executing jointly specific operations.…”

Section: Review Of Relevant Researchmentioning

confidence: 99%

Balancing of assembly lines with collaborative robots

Weckenborg

Kieckhäfer

Müller

et al. 2019

Bus Res

105

View full text Add to dashboard Cite

Motivated by recent developments to deploy collaborative robots in industrial production systems, we investigate the assembly line balancing problem with collaborative robots. The problem is characterized by the possibility that human and robots can simultaneously execute tasks at the same workpiece either in parallel or in collaboration. For this novel problem type, we present a mixed-integer programming formulation for balancing and scheduling of assembly lines with collaborative robots. The model decides on both the assignment of collaborative robots to stations and the distribution of workload to workers and robotic partners, aiming to minimize the cycle time. Given the high problem complexity, a hybrid genetic algorithm is presented as a solution procedure. Based on extensive computational experiments, the algorithm reveals promising results in both computational time and solution quality. Moreover, the results indicate that substantial productivity gains can be utilized by deploying collaborative robots in manual assembly lines. This holds especially true for a high average number of robots and tasks to be assigned to every station as well as a high portion of tasks that can be executed by the robot and in collaboration.

show abstract

“…Recently, a commonly used CGT method, the Shapley value (Shapley, 1953) has been applied to allocate emissions in cooperative transportation (Naber et al, 2015). However, the possibility to use CGT methods to allocate the economic benefits based on both the economic and environmental contribution of participants has not been explored; CGT methods have mainly been used either for economic or for environmental allocation (Guajardo, 2018). The objective of this study is to propose a methodology for allocating economic benefits of VMI based on both the economic and environmental contributions of participants, such that both contributions are rewarded and eco-efficient forms of cooperation are stimulated.…”

Section: Introductionmentioning

confidence: 99%