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The ocean transportation of automobiles is carried out by specialized Roll‐on/Roll‐off ships, which are designed to carry a large number of automobiles at a time. Many of these shipping companies have vertically integrated or collaborated with other logistics services providers to offer integrated maritime logistics solution to car manufacturers. The purpose of this study is to develop an optimization model to address the tactical level maritime logistics planning for such a company.

The problem is formulated as a mixed integer linear program and we propose an iterative combined Ant colony and linear programming‐based solution technique for the same.

This paper can integrate the maritime transportation planning of internally managed cargoes with the inventory management at the loading and discharging ports to minimize supply‐chain cost and also maximize additional revenue through optional cargoes using same fleet of ships.

The mathematical model does not consider the variability in production and consumption of products across various locations, travel times between different nodes, etc.

The suggested mathematical model to the supply‐chain planning problem and solution technique can be considered in the development of decision support system for operations planning.

This paper extends the maritime inventory routing model by considering simultaneous planning of optional cargoes with internally managed cargoes.

The purpose of this paper is to resolve three problems in ship routing and scheduling systems. Problem 1 is the anticipation of the future cargo transport demand when the shipping models are stochastic based on this demand. Problem 2 is the capacity of these models in processing large number of ships and cargoes within a reasonable time. Problem 3 is the viability of tramp shipping when it comes to real problems.

A commodity-trade forecasting system is developed, an information technology platform is designed and new shipping elements are added to the models to resolve tramp problems of en-route ship bunkering, low-tide port calls and hold-cleaning cost caused by carrying incompatible cargoes.

More realistic stochastic cargo quantity and freight can now be anticipated, larger number of ships and cargoes are now processed in time and shipping systems are becoming more viable.

More support goes to ship owners to make better shipping decisions.

New norms are established in forecasting, upscaling and viability in ship routing and scheduling systems.

Emissions produced by oceangoing vessels not only negatively affect the environment but also may deteriorate health of living organisms. Several regulations were released by the International Maritime Organization (IMO) to alleviate negative externalities from maritime transportation. Certain polluted areas were designated as “Emission Control Areas” (ECAs). However, IMO did not enforce any restrictions on the actual quantity of emissions that could be produced within ECAs. This paper aims to perform a comprehensive assessment of advantages and disadvantages from introducing restrictions on the emissions produced within ECAs. Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure. Numerical experiments demonstrate that introduction of emission restrictions within ECAs can significantly reduce pollution levels but may incur increasing route service cost for the liner shipping company.

Two mixed-integer non-linear mathematical programs are presented to model the existing IMO regulations and an alternative policy, which along with the established IMO requirements also enforces restrictions on the quantity of emissions produced within ECAs. A set of linearization techniques are applied to linearize both models, which are further solved using the dynamic secant approximation procedure.

Numerical experiments were conducted for the French Asia Line 3 route, served by CMA CGM liner shipping company and passing through ECAs with sulfur oxide control. It was found that introduction of emission restrictions reduced the quantity of sulfur dioxide emissions produced by 40.4 per cent. In the meantime, emission restrictions required the liner shipping company to decrease the vessel sailing speed not only at voyage legs within ECAs but also at the adjacent voyage legs, which increased the total vessel turnaround time and in turn increased the total route service cost by 7.8 per cent.

This study does not capture uncertainty in liner shipping operations.

The developed mathematical model can serve as an efficient practical tool for liner shipping companies in developing green vessel schedules, enhancing energy efficiency and improving environmental sustainability.

Researchers and practitioners seek for new mathematical models and environmental policies that may alleviate pollution from oceangoing vessels and improve energy efficiency. This study proposes two novel mathematical models for the green vessel scheduling problem in a liner shipping route with ECAs. The first model is based on the existing IMO regulations, whereas the second one along with the established IMO requirements enforces emission restrictions within ECAs. Extensive numerical experiments are performed to assess advantages and disadvantages from introducing emission restrictions within ECAs.

This study aims to examine ship loading strategies during large-scale military deployments. Ships are usually loaded to a stowage goal of about 65% of the ship's capacity. The authors identify how much cargo to load onto ships for each sailing and propose lower stowage goals that could improve the delivery of forces during the deployment.

The authors construct several mixed integer programs to identify optimal ship loading strategies that minimize delivery timelines for notional, but realistic, problem variables. The authors study the relative importance of these variables using experimental designs, regressions, correlations and chi-square tests of the empirical results.

The research specifies the conditions during which ships should be light loaded, i.e. loaded to less than 65% of total capacity. Empirical results show cargo delivered up to 16% faster with a light-loaded strategy compared to fully loaded ships.

This work assumes deterministic sailing times and ship loading times. Also, all timing aspects of the problem are estimated to the nearest natural number of days.

This research provides important new insights about optimal ship loading strategies, which were not previously quantified. More importantly, logistics planners could use these insights to reduce sealift delivery timelines during military deployments.

Most ship routing and scheduling problems minimize costs as the primary goal. This research identifies the situations in which ships transporting military forces should be light loaded, thereby trading efficiency for effectiveness, to enable faster overall delivery of unit equipment to theater seaports.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed.

The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe.

The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value.

The vessel carrying capacity is not considered in an explicit way.

This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.

This chapter explains the impact containerisation has on the various partners of the global supply chain and the challenges companies encounter and the solutions they use in dealing with empty container repositioning.

The phenomenon of imbalanced container flows and its impact on shipping lines, shippers, container haulage companies, port development and the economy are presented. Special attention is given to explain the many solutions companies use to reduce the impact of empty container repositioning, hence tracing out the past research that led to these solutions and pointing to potentially new research directions in the future.

Because of the widespread use of containerisation and the imbalanced container flows that results from globalisation, empty container repositioning will be an ongoing issue for the maritime logistics industry. Many solutions are being used, but there is room for improvement and more research is needed.

Empty container repositioning is an important issue but has not been deemed as such in the literature. This chapter explains the reasons it is important and that its impact is not limited to shipping lines only but affects the whole supply chain.

Resilient route selection for oversized cargoes, one of the general bulk cargoes, has not been adequately optimized in terms of using the Arctic route. This study solves the problem of selecting the optimal shipping routes for oversized cargoes from Busan (South Korea) to Balkhash (Kazakhstan).

The study used the consistent fuzzy preference relation (CFPR) method, which is used to solve multi-criteria decision-making (MCDM) and uncertainty problems, to tackle the route selection. This method involves three procedures: first, the critical factors and alternative routes were obtained by the previous literature and an in-depth interview of experts of oversized cargo-handling with more than 20 years of working experience; second, the weightings for each critical factor were identified using the CFPR calculation process and third, alternative routes were evaluated using weighted critical factors.

The Northern Sea Route (NSR) combined with the inland waterways of Russia and Kazakhstan was first suggested for bulk carriers that handle oversized cargoes. The NSR could be a suitable route from Busan to Cape Kamenny of the Russian transshipment seaport, where oversized cargoes will be transferred to the river barge at Cape Kamenny, covering 4,913 km from the latter to Balkhash of Kazakhstan via the Ob/Irtysh River.

This study equips stakeholders in route selection for cargoes with strategies and methods to improve transportation efficiently and enhance shipping routes between Asia and the Commonwealth of Independent States (CIS). In addition to oversized cargoes, coal and timber from Russia can be transported to Asia using inland waterways and the NSR, which can also be used to transport plant equipment for petroleum refineries among Asian countries.

This is the first study to evaluate the suitability of the Artic route for oversized cargoes from South Korea to Kazakhstan. It provides a comprehensive evaluation framework of multimodal shipping routes and offers references for decision-makers when dealing with similar problems.

This paper aims to address how to systematically address vulnerability in a maritime transportation system using a formal vulnerability assessment approach, create quantitative measures of disruption risk and test the effect of mitigating measures. These quantitative data are prerequisites for cost efficiency calculations, and may be obtained without requiring excessive resources.

Supply chain simulation using heuristics‐based planning tools offers an approach to quantify the impact of disruption scenarios and mitigating measures. This is used to enrich a risk‐based approach to maritime supply chain vulnerability assessment. Monte Carlo simulation is used to simulate a stochastic nature of disruptions.

The exemplary assessment of a maritime liquefied natural gas (LNG) transportation system illustrates the potential for providing quantitative data about the cost of disruptions and the effects of mitigating measures, which are foundations for more precise cost efficiency estimates.

This simulation was done on a simplified version of a real transportation system. For resource reasons, several simplifications were made, both with regards to modeling the transportation system and with the implementation of the formal vulnerability assessment framework. Nevertheless, the authors believe the paper serves to illustrate the approach and potential outcome.

Practitioners are provided with an approach to get more precise quantitative data on disruption costs and cost/efficiency of mitigating measures, providing background data for decisions on investing in reduction of supply chain vulnerability.

The combination of risk assessment methods and inventory routing simulation of maritime supply chain problems is a novelty. Quantifying vulnerability, effects of disruptions and effects of mitigating measures in maritime transportation systems contributes to a little‐researched area.