Simultaneous Planning of Liner Ship Speed Optimization, Fleet Deployment, Scheduling and Cargo Allocation with Container Transshipment

Due to a substantial growth in the world waterborne trade volumes and drastic changes in the global climate accounted for CO2 emissions, the shipping companies need to escalate their operational and energy efficiency. Therefore, a multi-objective mixed-integer non-linear programming (MINLP) model is proposed in this study to simultaneously determine the optimal service schedule, number of vessels in a fleet serving each route, vessel speed between two ports of call, and flow of cargo considering transshipment operations for each pair of origin-destination. This MINLP model presents a trade-off between economic and environmental aspects considering total shipping time and overall shipping cost as the two conflicting objectives. The shipping cost comprises of CO2 emission, fuel consumption and several operational costs where fuel consumption is determined using speed and load. Two efficient evolutionary algorithms: Nondominated Sorting Genetic Algorithm II (NSGA-II) and Online Clustering-based Evolutionary Algorithm (OCEA) are applied to attain the near-optimal solution of the proposed problem. Furthermore, six problem instances of different sizes are solved using these algorithms to validate the proposed model.Comment: 28 pages, 10 figure

A multi-agent framework for container booking and slot allocation in maritime shipping

Digitalization is constantly altering company paradigms and expanding cross-border supply chain prospects. Maritime transportation plays an increasingly essential part in the global supply network. Since maritime shipping services need to exchange a huge number of papers and paperwork across numerous companies, the usage of a unified platform for inter-organisational communication and information sharing is required. To develop an integrative, adaptive, and intelligent container booking system, a multi-agent architecture is designed in this article. The proposed architecture will aid the maritime industry in establishing real-time information interchange between autonomous agents, shippers, freight forwarders, and shipping lines. The process outlined in this paper reveals how the agents communicate with one another to resolve underlying inconsistencies. With the multi-agent framework, the article also presents a container slot optimisation problem considering market segmentation, different booking periods, heterogeneous containers and port congestion scenarios. Using this model the managers can find the booking limit for each type of containers and accordingly they can accept or reject the incoming booking requests. Furthermore, a simulated case study is also provided to validate the model

Liner Ship Freight Revenue and Fleet Deployment for Single Service

For single-liner ship service, this study optimizes containerized cargo revenue minus ship operating costs. The decisions to optimize the ship fleet and shipment plan are included in this proposed model. This optimization problem is formulated as a mixed-integer non-linear programming model and solved it using LINGO. The proposed model is applied to a liner service route provided in the computational study and the results are analyzed in case of different scenarios of container shipment demand and different freight rates

Optimal allocation of near-expiry food in a retailer-foodbank supply network with economic and environmental considerations: an aggregator's perspective

Wastage of perishable food products is a severe concern to society and needs to be addressed to ensure food security for all. Moreover, the food waste when sent to landfills, decomposes to produce greenhouse gases like methane and carbon dioxide. The emergence of food banks and aggregators has abated the problem of food wastage to a certain extent. An aggregator, which connects the retailers to the food banks, plays a critical role in ensuring that the food reaches the food banks on time. However, to ensure food security and reduce wastage of food, it is essential that food aggregators remain profitable. The aggregator has to determine the number of heterogeneous vehicles to hire from the market and allocate them their route on a daily basis depending on donations committed by the retailers and also take into account potential environmental impact from the decomposition of food waste and carbon emitted from hired vehicles. Hence, we propose decision support for aggregators, using data from an aggregator based in Turkey, which can help in reducing food wastage by allocating the donated food items from retailers to food banks while maximizing the profitability of the aggregator and minimizing the environmental impact. We have also analyzed how the availability of different types of vehicles can impact the aggregator's profit. Furthermore, the effect of various model parameters such as transportation cost, and percentage of retailers' gain paid to the aggregator on the total profit along with the impact of distances on types of vehicles hired is also analyzed. We have compared two strategies that the aggregator could possibly employ and generate managerial insights