Accession Number : AD0875913
Title : Ship-to-Shore Interface Analysis by Digital Simulation.
Descriptive Note : Final rept. 1 Sep 69-31 Aug 70,
Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE DEPT OF NAVAL ARCHITECTURE AND MARINE EN GINEERING
Personal Author(s) : Chryssostomidis, C.
Report Date : SEP 1970
Pagination or Media Count : 351
Abstract : Two tasks were considered. First was the development of the mathematical model simulating a cargo transportation interface in which the cargo is to be transported from a ship moored at some distance from the shore to point A on a beach where no port facilities are available. The transfer of cargo from the ship to the transfer vehicles is by ship-based unloading gear. The cargo transfer from the transfer vehicles at the shore is by beach-based unloading gear. The second was the selection of the solution method that would permit the analysis of such a mathematical model. Importance was attached to the condition that the solution method should enable the user to gain an insight into the unloading procedure and thence correctly derive the optimum use strategies. Computer digital simulation was chosen because it provides the necessary insight and also allows the user to solve the problem without needing drastic simplifications of the mathematical model, as required by known optimization techniques. For further usefulness, the concept of antithetic variance was introduced into the solution procedure. Since digital simulation is employed as the solution method in almost all congestion problems, it follows that antithetic variance may also be used profitably in models other than the one in this study. Guidelines for the user have therefore been included. (Author)
Descriptors : (*CARGO SHIPS, CARGO), (*CARGO, HANDLING), (*QUEUEING THEORY, MATHEMATICAL MODELS), COMPUTER PROGRAMS, MATHEMATICAL PROGRAMMING, TRANSPORTATION, DISTRIBUTION FUNCTIONS, TRANSFORMATIONS(MATHEMATICS), INTEGRAL EQUATIONS, DIFFERENTIAL EQUATIONS, STOCHASTIC PROCESSES, DECISION THEORY, SET THEORY, RANDOM VARIABLES, OPTIMIZATION, SIMULATION.
Subject Categories : Operations Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE