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In mathematics and economics, transportation theory or transport theory is a name given to the study of optimal transportation and allocation of resources. The problem was formalized by the French mathematician Gaspard Monge in 1781. [1] In the 1920s A.N. Tolstoi was one of the first to study the transportation problem mathematically.
That problem assumes that one has decided to take a trip, where that trip will go, and at what time the trip will be made. They have been used to treat the implied broader context. Typically, a nested model will be developed, say, starting with the probability of a trip being made, then examining the choice among places, and then mode choice.
Transshipment problems form a subgroup of transportation problems, where transshipment is allowed. In transshipment, transportation may or must go through intermediate nodes, possibly changing modes of transport. The Transshipment problem has its origins in medieval times [dubious – discuss] when trading started to become a mass phenomenon ...
This is an unbalanced assignment problem. One way to solve it is to invent a fourth dummy task, perhaps called "sitting still doing nothing", with a cost of 0 for the taxi assigned to it. This reduces the problem to a balanced assignment problem, which can then be solved in the usual way and still give the best solution to the problem.
Download as PDF; Printable version; In other projects ... move to sidebar hide. Transportation theory may refer to: Transportation theory (mathematics) ...
Transport puzzles are logistical puzzles, which often represent real-life transportation problems. The classic transport puzzle is the river crossing puzzle in which three objects are transported across a river one at time while avoiding leaving certain pairs of objects together. The term should not be confused with the usage of transport ...
This problem can be seen as a generalization of the linear assignment problem. [2] In words, the problem can be described as follows: An instance of the problem has a number of agents (i.e., cardinality parameter) and a number of job characteristics (i.e., dimensionality parameter) such as task, machine, time interval, etc. For example, an ...
In the theory of linear programming, a basic feasible solution (BFS) is a solution with a minimal set of non-zero variables.Geometrically, each BFS corresponds to a vertex of the polyhedron of feasible solutions.