Many names, all the same?

The variations of names reflect the partly technical, commercial and service packaging being part of the offering. Some of ARL's arl-shipping.com solutions are offered from the principle that the transport provider doesn't have to think of technical issues; there are no investments -only usage fees- and the solutions are serviced by ARL and their partners' IT professionals.

This means that it is easy and fast to get started, and that the costs can be directly related to the business benefits provided.

ARL's approach is to partner with a professional and recognized hosting partner already having the required physical infrastructure for hosting established, complement with change management and professional services by its own capable resources, and let the pricing reflect that many customers use the same solutions and thereby can share the costs.

In October 2007 ARL released their e-schedule platform; the first in a series of commercial solutions for the transport industry. e-Schedules, a solution hosted on the arl-shipping.com platform, allows a provider of a transport service to publish his schedule on the internet. The schedule is generated on the fly by the platform based on parameters entered by the transport provider like services start & end date, daily or weekly pattern, transit time per service point and closing & availability cut-off.

e-Schedule entails that the transport provider's customer ask for a departure or arrival matching specific requirements, rather than the transport provider to 'push' their in-house schedule to their customers.

The front office e-Schedule request is imbedded in the transport providers own web-site, powered by arl-shipping.com.

Low cost airlines entered the European airspace in 1991 when Ireland's Ryan Air commenced their operations. Later easyJet followed in 1995 and from 2000 a similar trend started in Asia. Aside from the leaders of the low cost airlines being financially successful in a tight market, they differentiate themselves from traditional airlines by a number of factors:

During a series of articles, we will explore a number of these differences -those facilitated by IT technology- and draw parallels to how the cargo industry is currently operating and may operate in the future.

During the 2-days event in Antwerp arranged by Millenium Conferences International, ARL's Evgeny Drokov gave a speech on the subject of berthing optimization based on the experiences from ARL's Berthing Optimizer.

The event was visited by shipping & transport professionals primarily from Europe and Africa.

• Berth position visualization
• Active vessels and yard data from TOS
• Manual adding of proforma vessel calls
• Mathematical, computer determined, optimized vessel berthing combined with manual drag & drop
• Berth unavailable zones
• Visualization of current and ideal berth location
• Visualization of gantry cranes reach
• Multiple scenarios in parallel
• Manual change of arrival/ departure time
• Determination of berth clashes
• Calculation of current and ideal mileage

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Whilst considering some physical conditions defining the possible berthing of a container vessel in port, like LOA of vessel, free space between vessels, vessel ETA & ETD, draught and tide, temporary unavailable berthing zones (non-working crane or quay under repair) vessels can be planned for berthing at a container terminal.

Combining these restrictions with knowledge about the physical characteristics of the yard (geometry, dimensions, yard driving rules), the actual location of containers ready for loading and assigned blocks for discharge containers, the assigned vessel berth can be optimized with the result of saved mileage of the yard equipment.

This optimization algorytm belongs to the NP-hard complexity class. This means that there is no exact effective algorithm known. Brute force algorithm, that finds all vessels' permutations (only relative vessel position, no exact coordinates, no traffic optimization) requires about 1018 combinations to be considered for moderately busy terminals with 20 calls per week. Such direct approach may take hours and even days just to find a feasible berthing scenario.

Wikipedia:

NP-hard (nondeterministic polynomial-time hard), in computational complexity theory, is a class of problems informally "at least as hard as the hardest problems in NP." A problem H is NP-hard if and only if there is an NP-complete problem L that is polynomial time Turing-reducible to H, i.e. . In other words, L can be solved in polynomial time by an oracle machine with an oracle for H.

The famous simplex method that successfully solves many real world problems cannot be applied to berthing optimization as it contains non-linear both constraints and target function, due to the yard equipment mileage calculation.

The solution was to build an effective approximation algorithm by incorporating algorithms from graphs theory and an inhouse developed algorithm for solving system of inequalities, that describes parameters of the task. It finds near to optimal solution in seconds:

The proposed algorithm starts with finding a feasible solution by solving a system of inequalities. This system reflects physical limitations such as total berth length, vessel length, minimal allowable distance between vessels, location of unavailable zones, etc. The solver not only places vessels to berth to meet all constraints, but also find vessel position among available positions resulting in minimal yard equipment mileage. The algorithm also uses vessel priority based on total amount of move operations to guarantee that "heavy" vessels get the best positions. Output of this stage is a feasible berthing scenario with reasonably good total mileage.

Next phase operates with graph representation of the berth scenario. It checks if small shift of vessel and all dependent vessels (that do not change order of vessels) give total mileage decrease. If mileage can be decreased by the vessel shift, the algorithm executes accordingly.

Then a set of heuristics is applied to the scenario. These heuristics defines rules of vessel permutations, that cannot break the scenario feasibility, but can result in mileage decrease. This phase completes final scenario tuning.

An important advantage of the approach is that it allows adjusting almost any parameter manually and letting others to be found by the algorithm. Additionally, the structure of the algorithm allows adaption to new business requirements. This results in flexibility in practical applications.

During recent years ARL Consulting have completed several projects incorporating complex mathematical models as an integral part of the solution provided. This is in response to the continously increasing unit counts in shipping and transport, like growing size of vessels, number of transports, number of hub-and-spoke connection opportunities, which makes it harder and harder to identify and evaluate multiple options by human force only.

In a series of shipZine articles three business challenges in the transport industry, which has been successfully resolved by applying scientific approaches, will be explored:

1. selection of optimal container vessel berthing at quay side
2. evaluation of relevant vessel deployment opportunities
3. vessel bunker consumption calculation

Each of the business scenarios provide benefits for the transportation organisation: 

1) selection of optimal container vessel berthing reduce the mileage required by the yard equipment for servicing the vessel; this results in direct fuel savings, time savings for equipment drivers, reduces wear-and-tear and allow for servicing of more vessels with the same amount of equipment and staff. 

2) evaluation of relevant vessel deployment opportunities provides the deployment planners with the ability to consider feasible and relevant network and deployment scenarios, which can be assessed from an operational and commercial perspective, not only saving time with the planners, but highlighting deployment scenarios, with benefical cost and income opportunities, which otherwise would not have been considered due to the complexity of the many opportunities.

3) vessel bunker consumption calculation give the direct benefit of reduced bunkers costs.

brute force - Free On-Line Dictionary of Computing:

<programming> A primitive programming style in which the programmer relies on the computer's processing power instead of using his own intelligence to simplify the problem, often ignoring problems of scale and applying naive methods suited to small problems directly to large ones. The term can also be used in reference to programming style: brute-force programs are written in a heavy-handed, tedious way, full of repetition and devoid of any elegance or useful abstraction

The mathemathical approaches used are all 'intelligent' alternatives to clean brute-force approach and reflect in some form that the computer system act as a human thinking brain -just much faster and more comprehensive.

Many other areas for harvesting benefit by using math force, like container vessel stowage planning, exist in the transport industry.

During the bi-annual Bangkok event arranged by Transport Events Management, ARL Director Rene Bendt, gave a speech on the subject of 'Electronic Capacity & Price Management' - the presentation is available online.

Thai Minister of Transport visiting ARL Consulting exhibition stand in Bangkok

The event was visited by shipping & transport professionals primarily from South East Asia and ARL Consulting additional had a stand demonstrating some of their solutions for the shipping & transport industry.