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Due to a substantial growth in the world waterborne trade volumes and drasticchanges in the global climate accounted for CO2 emissions, the shippingcompanies need to escalate their operational and energy efficiency. Therefore,a multi-objective mixed-integer non-linear programming (MINLP) model isproposed in this study to simultaneously determine the optimal serviceschedule, number of vessels in a fleet serving each route, vessel speed betweentwo ports of call, and flow of cargo considering transshipment operations foreach pair of origin-destination. This MINLP model presents a trade-off betweeneconomic and environmental aspects considering total shipping time and overallshipping cost as the two conflicting objectives. The shipping cost comprises ofCO2 emission, fuel consumption and several operational costs where fuelconsumption is determined using speed and load. Two efficient evolutionaryalgorithms: Nondominated Sorting Genetic Algorithm II (NSGA-II) and OnlineClustering-based Evolutionary Algorithm (OCEA) are applied to attain thenear-optimal solution of the proposed problem. Furthermore, six probleminstances of different sizes are solved using these algorithms to validate theproposed model.

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