Shipping Optimisation Systems (SOS): tramp optimisation perspective

Abstract

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.

The implication of the stochastic gross-profit-per-day objective on the cargo ship profitability, capacity, and speed

“…The mathematical model and the solution methodology for the tramp shipping are included in El Noshokaty, 2017a, 2017band SOS, 2019; and for the liner shipping in El Noshokaty, 2013 and SOS, 2019. Shipping Optimization Systems (SOS) is a suite of decision support systems which comprises a database management system incorporated with the aforementioned mathematical models.…”

“…Review of the literature To review the possible effects of the gross profit and the gross profit-per-day objectives on the ship profitability, the reader is to refer to El Noshokaty, 2013, 2017b for the liner shipping and El Noshokaty, 2014, 2017a, 2017b, 2018c for the tramp shipping. The former papers recommend the optimization of a stochastic gross profit objective while the latter papers recommend the optimization of a stochastic gross profit-per-day objective, rather than a deterministic gross profit one.…”

“…In shipping, the gross-profit-per-day objective implies the fact that the ship voyage is variable in time, the case which occurs when the ship is following the tramp mode of operation, or, when the ship capacity and speed are strategically subject to selection either in the tramp or liner mode of operation. El Noshokaty, 2017aNoshokaty, , 2017b has developed the mathematical models to optimize a stochastic gross profit-per-day objective for the time-variable ship voyage. It also applies sensitivity and what-if analysis if there are any possible changes that might happen to cargo quantity and freight, cargo handling rate and charges, and ship speed and fuel consumption.…”

“…Nothing of the above-mentioned findings has to do with the efficiency of the mega-ships and whether these ships are following the efficiency rates as described in the third section. The paper uses the same mathematical model and the solution methodology developed by El Noshokaty, 2017a, 2017b. A case study is given to demonstrate a possible magnitude of the implication of the stochastic gross-profit-per-day objective in the tramp shipping.…”

Shipping digitalization management: conceptualization, typology and antecedents

“…Extant research offers an important knowledge base, in view of various types of information technology applications used in shipping, trade and transport. A broad range of decision support systems for shipping operational optimization (El Noshokaty, 2017), information systems for port logistics support (Mlimbila and Mbamba, 2018), and tools for policy-makers (Szimba et al, 2018) constitute the legacy of contemporary shipping digitalization. Our study addresses the following primary research questions: which are the effectual technologies of contemporary shipping digitalization and how these technologies resonate in shipping management; which management logics necessitate the adoption of digital technologies in shipping and which digitalization management practices enable them.…”