Optimization of Ship Cargo Operations by Genetic Algorithm

Hess, Svjetlana; Hess, Mirano

doi:10.7307/ptt.v21i4.231

Cited by 4 publications

(7 citation statements)

References 12 publications

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“…ship's cranes, forklifts and workers, with the objective of minimizing the total operational costs (Hess, S., Hess, M. 2009) may prove to be a hard task. Furthermore, the added complexity arises if the ship's operator considers such costs confronted to total earnings in the broader context of business making, in time period that extends ship's stay at port.…”

Section: The Problemmentioning

confidence: 99%

“…As highlighted in the paper by Hess, S. and Hess, M. (2009) ship can be defined as a mass servicing system where the arrival rate of units, parameter λ, represents the average number of general cargo units arrived alongside the ship during an observed time unit (e.g. during a year, month or day).…”

Section: Mathematical Dependencesmentioning

confidence: 99%

“…Service time of ship's cargo cranes, forklifts and longshoremen, as well as, sequence of cargo units' arrival alongside the ship follow certain probability distributions (Van Asperen et al 2003;Hess, S., Hess, M. 2010;Hess, M., Hess, S. 2011). In this paper the general cargo ship is defined as a multichannel, multiphase mass service system, where the input flow of general cargo passes through the four phases in the process of cargo handling (Hess, S., Hess, M. 2009). When making business decisions related to these processes (Hess et al 2007(Hess et al , 2008Machuca et al 2007), it is essential for the ship's operator to achieve the minimum transhipment costs and costs of the ship's stay in port together with minimum service time.…”

Section: Introductionmentioning

confidence: 98%

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Multi-Objective Ship’s Cargo Handling Model

Hess

2013

Transport

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This paper proposes a new optimization model for ship's cargo handling operations which solution gives the structure of cargo handling resources required, along with attaining the minimum total 'in-port' costs and the minimum of time required for completion of cargo operations. Due to complexity of the model which consists of composite multi-objective functions together with several decision variables and constraints, the solution has been sought by utilization of an adapted genetic algorithm combined with a hybrid algorithm. Testing of the model on real world data yielded acceptable results in a short time. In the course of decision making, the ship's operator can, on the basis of the proposed model and taking into consideration shipping market data, choose appropriate variation of the returned solution, which incorporates minimum costs, minimum of operational time and related cargo handling resources.

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Section: The Problemmentioning

confidence: 99%

Section: Mathematical Dependencesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Multi-Objective Ship’s Cargo Handling Model

Hess

2013

Transport

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“…Considering operating processes in the port terminal (Hess, Hess 2009), three basic states when a terminal can be found at a given moment can be distinguished: Sj -standby state (no working operation on the wharf, but the collection and analysis of data regarding cargo, vessel and weather); 52 -operating state (cargo loading and unloading, cargo dispatching from the operating wharf to warehouses or inland means of transport; this is the most favourable state economically); 53 -intermission state (regular maintenance of TTE, repairs in case of a sudden fault, break in case of bad weather which prevents from safe transshipment actions, break due to possible workers' strikes, postponement of work due to vessel or cargo delay from the inland).…”

Section: Model Setupmentioning

confidence: 99%

Assignment of Stochastic Models for the Domain of Port Terminal Operations / Stochastinių Modelių Taikymas, Atliekant Operacijas Uosto Terminale / Применение Стохастических Моделей Для Выполнения Операций В Портовом Терминале

Hess

2011

Transport

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The paper presents the optimization possibilities of port terminal operations in order to generate maximum gain. Planning tbese processes is a demanding daily task taken on before dealing with port management, since transhipment operations, cargo loading and dispatching, maintenance and control of transhipment and transportation means are subject to hardly predictable and unexpectable stochastic conditions under which planning optimal terminal operations will include the examination of stochastic processes on the terminal. A model of states and transitions with gain and a model of optimal strategies in terminal management are set up. Furthermore, a model for determining the structure of transhipment equipment is developed. The devised models were adapted to the specificities of a port terminal and tested using the sample of a general cargo terminal.

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“…Such models and the search for their solution lie in the complexity of mathematical calculations and finding of the optimum due to composite form of the objective function which contains several decision variables and constraints in a large solution space [16]. The plan for transhipment and transport of cargo is determined as a part of the plan of implementing port services, as it represents a solution for the cargo transhipment problem.…”

Section: Model Of Transhipment Processes At the Container Terminalmentioning

confidence: 99%