Risk management in liner ship fleet deployment: A joint chance constrained programming model

This paper provides a tangible methodology to deal with the liner ship fleet deployment problem aiming at minimizing the total cost while maintaining a service level under uncertain container demand. The problem is first formulated as a joint chance constrained programming model, and the sample average approximation method and mixed-integer programming are used to deal with it. Finally, a numerical example of a liner shipping network is carried out to verify the applicability of the proposed model and solution algorithm. It is found that the service level has significant effect on the total cost.     

Minimizing fuel emissions by optimizing vessel schedules in liner shipping with uncertain port times

We consider the problem of designing an optimal vessel schedule in the liner shipping route to minimize the total expected fuel consumption (and emissions) considering uncertain port times and frequency requirements on the liner schedule. The general optimal scheduling problem is formulated and tackled by simulation-based stochastic approximation methods. For special cases subject to the constraint of 100% service level, we prove the convexity and continuous differentiability of the objective function. Structural properties of the optimal schedule under certain conditions are obtained with useful managerial insights regarding the impact of port uncertainties. Case studies are given to illustrate the results.     

Measuring the perceived container leasing prices in liner shipping network design with empty container repositioning

This paper aims to measure the perceived container leasing prices at different ports by presenting a two-stage optimization method. In stage I, we propose a practical liner shipping network design problem with empty container repositioning. The proposed problem further considers the use of foldable containers and allows the mutual substitution between empty containers to decrease the number of empty containers to be repositioned. In stage II, the inverse optimization technique is used to determine the perceived container leasing prices at different ports, based on the solution obtained in stage I. Based on a set of candidate liner shipping service routes, a mixed-integer nonlinear programming model is built for the proposed problem in stage I. The nonlinear terms are linearized by introducing the auxiliary variables. Numerical experiments based on a realistic Asia-Europe-Oceania liner shipping network are carried out to account for the effectiveness of our two-stage optimization method.     

Container fleet sizing and empty repositioning in liner shipping systems

This paper considers the joint container fleet sizing and empty container repositioning problem in multi-vessel, multi-port and multi-voyage shipping systems with dynamic, uncertain and imbalanced customer demands. The objective is to minimize the expected total costs including inventory-holding costs, lifting-on/lifting-off costs, transportation costs, repositioning costs, and lost-sale penalty costs. A simulation-based optimization tool is developed to optimize the container fleet size and the parameterized empty repositioning policy simultaneously. The optimization procedure is based on Genetic Algorithms and Evolutionary Strategy combined with an adjustment mechanism. Case studies are given to demonstrate the results.     

The container shipping network design problem with empty container repositioning

This paper addresses the design of container liner shipping service networks by explicitly taking into account empty container repositioning. Two key and interrelated issues, those of deploying ships and containers are usually treated separately by most existing studies on shipping network design. In this paper, both issues are considered simultaneously. The problem is formulated as a two-stage problem. A genetic algorithm-based heuristic is developed for the problem. Through a number of numerical experiments that were conducted it was shown that the problem with the consideration of empty container repositioning provides a more insightful solution than the one without.     

Liner ship fleet deployment with container transshipment operations

This paper proposes a liner ship fleet deployment (LSFD) problem with container transshipment operations. The proposed problem is formulated as a mixed-integer linear programming model which allows container transshipment operations at any port, any number of times, without explicitly defining the container transshipment variables. Experiments on the Asia-Europe-Oceania shipping network of a global liner shipping company show that more than one third (17-22 ports) of the total of 46 ports have transshipment throughputs. Computational studies based on randomly generated large-scale shipping networks demonstrate that the proposed model can be solved efficiently by CPLEX.     

Combined fleet deployment and inventory management in roll-on/roll-off shipping

In maritime transportation of automobiles, roll-on/roll-off (ro–ro) shipping companies operate liner shipping services across major trade routes. Large ro–ro shipping companies are well placed to offer end-to-end integrated logistics services to auto manufacturers engaged in international trade of vehicles. Therefore, we present a new mixed integer programming model for fleet deployment including inventory management at the ports along each trade route. Due to the complexity of the problem, a rolling horizon heuristic (RHH) is proposed. The RHH solves the problem by iteratively solving sub-problems with shorter planning horizon. Computational results based on real instances are presented.     

Liner hub-and-spoke shipping network design

This paper proposes a liner hub-and-spoke shipping network design problem by introducing the concept of a main port, as well as some container shipping constraints such as multi-type container shipment and transit time constraints, which are seldom considered in the previous studies. It develops a mixed-integer programming model with nonconvex multi-linear terms for the proposed problem. An efficient genetic algorithm embedded with a multi-stage decomposition approach is developed to solve the model. Numerical experiments are carried out to assess the effectiveness of the proposed model and the efficiency of the proposed algorithm.     

A novel modeling approach for the fleet deployment problem within a short-term planning horizon

This paper is concerned with model development for a short-term fleet deployment problem of liner shipping operations. We first present a mixed integer nonlinear programming model in which the optimal vessel speeds for different vessel types on different routes are interpreted as their realistic optimal travel times. We then linearize the proposed nonlinear model and obtain a mixed integer linear programming (MILP) model that can be efficiently solved by a standard mixed integer programming solver such as CPLEX. The MILP model determines the optimal route service frequency pattern and take into account the time window constraints of shipping services. Finally, we report our numerical results and performance of CPLEX on randomly generated instances.     

A novel hybrid-link-based container routing model

Container routing determines how to transport containers from their origins to their destinations in a liner shipping network. Container routing needs to be solved a number of times as a subproblem in tactical-level decision planning of liner shipping operations. Container routing is similar to the multi-commodity flow problem. This research proposes a novel hybrid-link-based model that nests the existing origin-link-based and destination-link-based models as special cases. Moreover, the hybrid-link-based model is at least as compact as the origin-to-destination-link-based, origin-link-based and destination-link-based models in the literature.     

Global intermodal liner shipping network design

This paper presents a holistic analysis for the network design problem of the intermodal liner shipping system. Existing methods for liner shipping network design mainly deal with port-to-port demand. However, most of the demand has inland origins and/or destinations. Thus, it is necessary to cope with inland origin–destination (OD) pairs involving a change in transport mode from inland transportation to maritime shipping. A method is first proposed to convert inland OD demand to port-to-port demand. Then, a framework for global intermodal liner shipping network design is proposed. Finally, the proposed methodology is applied to and numerically verified by a large-scale network example.     

Shipping efficiency comparison between Northern Sea Route and the conventional Asia-Europe shipping route via Suez Canal

The continuous retreat of Arctic sea ice and seemingly appealing cost competitiveness of transarctic shipping routes are expected to boost shipping activities in the region. However, in reality, the number of Arctic transits remains meagre compared with major shipping routes. This study first develops a profit estimation model for containership sailing from an original port to a destination port with multiple port calls and a cost estimation model for oil tanker sailing from an origin port to a destination port. The authors then proceed to compare the shipping efficiency between the Northern Sea Route (NSR) and the Asia-Europe shipping route via Suez Canal by using the developed models and real shipping operational data. The results demonstrate that NSR shipping is not economically favored compared to traditional one in container shipping, but may be only appealing to small or medium-size tanker operators.     

Estimating attributes importance for container shipping industry by closing the listening gap with maximum convergent validity

This paper estimates the relationship of attributes importance (AI) to prospect purchase intention by closing the listening gap between customers and managers of container shipping companies. A proposition of minimum cross entropy is proposed to find a solution to the problem with maximum convergent validity, and this proposition is used to estimate AI, in which both opinions about AI of customers and managers of container shipping companies are included. Results indicate that price, discount, personal selling, and word of mouth, are the most important attributes to prospect purchase intention, within the industry. In addition, managerial implications are also discussed.     

Shipping design for compliance and the performance contingencies for shipping firms

Increasing number of shipping firms adopt green shipping practices that emphasize environmental management throughout their operations. To balance productivity with the environment, the design of shipping activities in compliance with energy saving and resources conversation is an important part of greening efforts by many shipping firms. This study investigates how the green practices on shipping design for compliance (SDC) adopted by shipping firms is related to their financial and service performance with the role of company policy and procedures and shipper cooperation examined. We find that SDC is beneficial for the financial and service performance of shipping firms. Based on the contingency theory, we argue further that company policy and procedure as well as shipper cooperation differentiates the performance outcomes of shipping firms in their SDC for environmental management. Our empirical findings show a positive relationship of SDC with service performance particularly when their company policy and procedure and shipper cooperation are characterized at high than low levels in the process. However, such strengthening effects are not found for the relationship between SDC and the financial performance of shipping firms.     

Sailing speed optimization for container ships in a liner shipping network

This paper first calibrates the bunker consumption - sailing speed relation for container ships using historical operating data from a global liner shipping company. It proceeds to investigate the optimal sailing speed of container ships on each leg of each ship route in a liner shipping network while considering transshipment and container routing. This problem is formulated as a mixed-integer nonlinear programming model. In view of the convexity, non-negativity, and univariate properties of the bunker consumption function, an efficient outer-approximation method is proposed to obtain an ε-optimal solution with a predetermined optimality tolerance level ε. The proposed model and algorithm is applied to a real case study for a global liner shipping company.     

The time constrained multi-commodity network flow problem and its application to liner shipping network design

The multi-commodity network flow problem is an important sub-problem in several heuristics and exact methods for designing route networks for container ships. The sub-problem decides how cargoes should be transported through the network provided by shipping routes. This paper studies the multi-commodity network flow problem with transit time constraints which puts limits on the duration of the transit of the commodities through the network. It is shown that for the particular application it does not increase the solution time to include the transit time constraints and that including the transit time is essential to offer customers a competitive product.     

Hub location problems in transportation networks

In this paper we propose a 4-index formulation for the uncapacitated multiple allocation hub location problem tailored for urban transport and liner shipping network design. This formulation is very tight and most of the tractable instances for MIP solvers are optimally solvable at the root node. While the existing state-of-the-art MIP solvers fail to solve even small size instances of problem, our accelerated and efficient primal (Benders) decomposition solves larger ones. In addition, a very efficient greedy heuristic, proven to be capable of obtaining high quality solutions, is proposed. We also introduce fixed cost values for Australian Post (AP) dataset.     

Liner shipping cargo allocation with service levels and speed optimization

The cargo allocation problem is a key strategic problem that determines the profitability of a liner shipping network. We present a novel mixed-integer programming model for this problem that introduces service levels for transit time requirements and optimizes the vessel speed on each leg of a service. These extensions to the cargo allocation problem greatly increase its realism and value for carriers. We evaluate our model on realistic data from the LINER-LIB and perform a sensitivity analysis of transit times versus bunker costs. Furthermore, we show how carriers can use our model to make data driven decisions in their operations.     

Multi-objective optimization for planning liner shipping service with uncertain port times

This paper considers a joint tactical planning problem for the number of ships, the planned maximum sailing speed, and the liner service schedule in order to simultaneously optimize the expected cost, the service reliability and the shipping emission in the presence of port time uncertainty. The problem is formulated into a stochastic multi-objective optimization problem at the operational level. The relationships between the objectives and the decision variables are established. A simulation-based non-dominated sorting genetic algorithm is then presented to solve this problem. A case study is provided to illustrate the results and the application of the model.     

Cooperation through capacity sharing between competing forwarders

In this paper, we consider a shipping system consisting of one carrier and two shipping forwarders who compete on price for businesses from potential shippers. The carrier may quote different prices or a single price to the two shipping forwarders who will then order shipping capacity from the carrier and set the selling prices to the shippers before market uncertainties are revealed. Inspired by cooperation between competing parties in many industries including the maritime shipping industry, we propose a new model under which the shipping forwarders are allowed an opportunity to purchase shipping capacity from each other after they order capacity from the carrier but before they set the selling prices and satisfy demand, referred to as the capacity reservation model. We show analytically that capacity reservation between competing forwarders benefits both the carrier and the forwarders, leading to a win–win situation under various market conditions. Furthermore, capacity reservation can offset the negative effect of a carrier’s pricing power which enables the carrier to charge discriminatory shipping prices to squeeze more profits out of the forwarders.