Titlebook: Operations Research; A Model-Based Approa H. A. Eiselt,Carl-Louis Sandblom Textbook 20122nd edition Springer-Verlag GmbH Germany, part of S

繼而發(fā)生

Multiobjective Programming,lt is an optimal solution (or multiple optima, in case of dual degeneracy). However, the concept of optimality applies only in case of a single objective. If we state that something is “the best” or optimal, we always have an objective in mind: the fastest car, the most comfortable vehicle, the auto

Crater

mechanism

Network Models,berg bridge problem.” At that time, there were seven bridges across the River Pregel that ran through the city of K?nigsberg on the Baltic Sea, and Euler wondered whether or not it would be possible to start somewhere in the city, walk across each of the bridges exactly once, and return to where he

Meander

Connotation

Machine Scheduling, doctor treating patients the doctor is the processor and the patients represent the tasks, in the case of a tax auditor the auditor is the processor (or the “machine”), while the individual cases are the tasks to be processed. This allocation is to be made so as to optimize some objective. We will

手勢(shì)

Decision Analysis,hat to eat for lunch or dinner, what to do in the evening (go to the theater or watch television), where to vacation, and many more. Similarly, firms will decide which mode of transportation to use when routing their products to customers, where to locate regional distribution centers, what new prod

jagged

Multicriteria Decision Making,t to the scenario in decision analysis, the outcomes are again deterministic. In other words, if we were to, say, change the composition of a soft drink we manufacture or change the controls on a television, we do not just deal with profit as a result of this decision, but face changing customer acc

hemorrhage

Inventory Models,nd outflow of goods. Inventories can be thought of as water tanks: there may be a constant inflow of water that is pumped into the tank by a pump, while the outflow is low at night, high in the morning (when people get up, take a shower, etc.), it then decreases significantly until the demand again

BANAL

Stochastic Processes and Markov Chains,ocesses, events occur over time. Time can be dealt with either in continuous fashion, or in discrete fashion. In the continuous case, we may look at the speed of an automobile at any given point in time or at the inventory level of a product in a supermarket at any time. In the discrete case, speed

Muscularis

Waiting Line Models,l experienced lineups in banks and supermarkets, but there are many more instances with waiting lines: think, for instance, about traffic lights, where drivers line up and wait, files that wait for processing in the inbox at a clerk’s workstation, or telephone calls that are put in a queue. Queuing