Cargo Mix Research Articles

Factors Influencing Greenhouse Gas Reduction Measures in European Ports: Implications for Sustainable Investing

European Union cargo and container ports are under pressure to reduce GHG emissions and achieve carbon neutrality by 2050, as mandated by the European Commission. The pace of progress varies among ports. This study examined the characteristics influencing GHG reduction measures in European cargo and container ports and their implications for sustainable investing. The methods used in this study, such as linear regression models to analyze predictive variables, can be applied in sustainable investing to assess which factors most strongly predict a company’s environmental, social, and governance performance. Using linear regression models to analyze data from the 33 busiest European ports, we identified five predictive variables: port size, cargo mix, surrounding population density, access to the sea, and the economic wealth of the host country. Our findings revealed that the port size significantly correlates with the adoption of measures to reduce scope 1, 2, and 3 emissions. This study underscores the importance of contextual and operational factors in evaluating sustainability efforts across sectors. The results contribute to drawing parallels with the field of sustainable investing within finance. This offers valuable insights for sustainable investing, emphasizing the importance of considering various contextual and operational factors when evaluating the sustainability efforts of entities in different sectors.

Including Containers with Dangerous Goods in the Cargo Mix Problem for Container Vessel Stowage

The Cargo Mix Problem (CMP) chooses and distributes types of containers to load into bay subsections of a container vessel. In this paper, we extend existing Mixed Integer Programming models for the CMP by considering containers with dangerous goods. We show that our model can be optimally solved in reasonable time using standard software.

Containership cargo profiles, cargo systems, and stowage capacity: key performance indicators

Being fit for purpose is a key element of a cargo system (or ship configuration). It is important to understand a certain cargo profile (or cargo mix) and to build a match between cargo profile and cargo system. The actual maximum capacity utilization of a ship is determined by the compatibility of these two factors. These operational questions are related to the planning and execution of stowage. The objective of this paper is to review container stowage metrics; demonstrate how a cargo profile may affect the productivity of the ship; and, finally, to propose a new metric to evaluate the effectiveness of ship stowage. Our metric is presented through a practical example.

Shipping Optimisation Systems (SOS): tramp optimisation perspective

This research paper is to announce a new policy to all systems which are sensitive to time. In tramp cargo transportation, as an example, the current policy is to select for each ship the cargo mix which contributes more to a gross-profit objective, assuming deterministic cargo transport demand. Since tramp cargo transportation is sensitive to time, where time varies considerably from one alternative ship voyage to another. The new policy considers this objective less profitable than gross-profit-per-day objective, assuming both deterministic and stochastic cargo transport demand. To introduce this new policy, SOS; a suite of decision support systems, is developed to optimise tramp shipping using a stochastic gross-profit-per-day objective. For operational purposes, SOS selects the most profitable cargo mix. This mix is selected because of the higher gross profit it is expected to yield and the less number of days it takes to generate such profit. For long-term planning purposes, SOS uses the optimal gross profit of each ship voyage, created by the system, to allocate fleet units to cargo trade areas, specifying their frequency of calls to maximise fleet annual gross profit. A useful application of this fleet allocation is that the allocated frequency of calls may be considered as representing the demand on services of utilities of ports, canals, and straits, and may be used to assess the competitiveness of these utilities. Utility and logistics planner, via sensitivity and what-if analysis, can determine whether calling at a utility of a trade area is sensitive to changes made to utility dues and staying time, cargo quantities and freight rates, cargo handling rates and charges, and ship speed and fuel consumption. For appraising purposes, SOS includes new ships in the allocation process, in competition with old ones, to find the share each new ship adds to total gross profit each year. SOS then applies the Net Present Value formula to gross profit of each new ship, along with other cash flow and cost of investment. SOS similar systems may be tailored for other means of cargo transport; namely cargo airplanes, trains, and trucks. The impact of SOS on any logistics and supply chain system is that it maintains the shortest possible transportation time owners of transport units can afford. Case studies are brought to demonstrate research findings.

Productivity growth in urban freight transport: An index number approach

Improvement of operational efficiency is a common goal of most governmental freight transport policies. Productivity and efficiency analysis consequently provides a sound knowledge base. This paper illustrates how axiomatic production theory can be applied to model road freight transport, and proposes a logistics efficiency measure as the function representation. Based thereon, a logistics productivity index that decomposes into technical, cargo mix, vehicle capacity, and efficiency changes is established to determine the rate and drivers of growth. Emphasizing urban logistics, the paper discusses the limited access to reliable data at the micro level and illustrates how local or regional freight transport can be evaluated applying pseudo panel techniques to national freight surveys. Correspondingly, the theoretical productivity index is implemented on a pseudo panel covering the 24 largest cities in Norway between 2008 and 2012, when 12 of them entered a collaboration agreement to promote efficient transport. The results indicate a modest 0.6% average productivity growth. Efficiency change is the key driver of growth, countered by technical stagnation and regress. Negative productivity growth is expected if this trend continues. Moreover, the results do not reveal productivity gains from urban agglomeration or membership of the collaboration agreement, suggesting that prevailing transport and land use policies have so far been unable to foster productivity growth in urban freight transport.

A matheuristic for the Cargo Mix Problem with Block Stowage

The cargo-mix problem aims at selecting the amount of containers of a given type to load on a vessel. In this article we present an extended definition that includes the analysis of a circular route with draft restrictions, limitations on expected cargo and the use of a block stowage strategy. A compact formulation of the problem based on the state-of-the-art heuristic decomposition is shown not to be able to solve the extended problem, thus a matheuristic approach is presented that can achieve high quality results in a matter of seconds.

Efficiency drivers in the Brazilian trucking industry: a longitudinal study from 2002-2010

Purpose – The purpose of this paper is to investigate the issue of efficiency in the Brazilian motor carrier industry, which has undergone significant transformations since the economy deregulation in the mid-1990s. The main research objective is to determine whether or not different types of cargoes and geographic regions serviced significantly impact trucking managerial efficiency levels. Design/methodology/approach – Research objectives are accomplished by applying a two-stage data envelopment analysis model with bootstrapped estimates. Based on an unbalanced panel model, secondary data from the annual study published by Transporte Moderno (years 2002-2010) were collected and analyzed. Findings – Results support anecdotal evidence regarding a heterogeneous impact of cargo mix and route mix on efficiency levels. Research limitations/implications – A major limitation of this work concerns the fact of working with secondary data instead of primary data, especially with respect to the set of inputs and out...

Measuring efficiency improvement in Brazilian trucking: A Distance Friction Minimization approach with fixed factors

This paper investigates paths for improving efficiency in the Brazilian motor carrier industry, which has undergone significant transformations since the economy deregulation in the mid 1990s. The main research objective is to determine whether or not different types of cargoes and geographic regions serviced significantly impact trucking efficiency levels by applying a Distance Friction Minimization approach with fixed factors. Results support the evidence regarding a heterogeneous impact of cargo mix and route mix on input reducing and output increasing potentials. Managerial impacts in terms of fleet subcontracting and increased focus on specific transport demands are also addressed.

An empirical study of the impacts of operating and market conditions on container-port efficiency and benchmarking

Despite the growing amount of research on container-port efficiency and benchmarking, the literature on the subject is yet to provide stable and consistent results across researchers and in relation to dynamic operating and market conditions. In this paper, we formulate a number of operational hypotheses to test the sensitivity of benchmarking results to port market and operating conditions namely production scale, cargo mix, transhipment ratio, operating configurations, and working procedures. A series of data envelopment analysis (DEA) models are used to measure the operational efficiency of 420 container terminal decision-making units from 2004 till 2010. The results show that variations in operating conditions highly impact terminal efficiency and that future work on container-port performance and benchmarking should take into account the structure and mechanisms underpinning the operations of container ports and terminals.

Two-Stage Stochastic Integer Programming Model for Multiperiod Sea Cargo Mix Problem in Container Shipping Industry

In this paper, we consider the cargo mix problem under uncertainty in the container shipping industry. We seek to determine the optimal cargo mix in a multiperiod planning horizon with the objective of maximizing the total expected profit derived from all freight bookings received in the planning horizon. We present a two-stage stochastic integer programming model and propose a heuristic algorithm for multiperiod sea cargo mix problem under uncertainty. Finally, numerical experiments on a wide range of randomly generated problem instances are conducted to demonstrate the efficiency of the algorithm.

Model and algorithms for multi-period sea cargo mix problem

In this paper, we consider the sea cargo mix problem in international ocean container shipping industry. We describe the characteristics of the cargo mix problem for the carrier in a multi-period planning horizon, and formulate it as a multi-dimensional multiple knapsack problem (MDMKP). In particular, the MDMKP is an optimization model that maximizes the total profit generated by all freight bookings accepted in a multi-period planning horizon subject to the limited shipping capacities. We propose two heuristic algorithms that can solve large scale problems with tens of thousands of decision variables in a short time. Finally, numerical experiments on a wide range of randomly generated problem instances are conducted to demonstrate the efficiency of the algorithms.