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Arc Routing Problem
Arc routing problems (ARP) are a category of general routing problems (GRP), which also includes node routing problems (NRP). The objective in ARPs and NRPs is to traverse the edges and nodes of a graph, respectively. The objective of arc routing problems involves minimizing the total distance and time, which often involves minimizing deadheading time, the time it takes to reach a destination. Arc routing problems can be applied to garbage collection, school bus route planning, package and newspaper delivery, deicing and snow removal with winter service vehicles that sprinkle salt on the road, mail delivery, network maintenance, street sweeping, police and security guard patrolling, and snow ploughing. Arc routings problems are NP hard, as opposed to route inspection problems that can be solved in polynomial-time. For a real-world example of arc routing problem solving, Cristina R. Delgado Serna & Joaquín Pacheco Bonrostro applied approximation algorithms to find the best ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Dead Mileage
Dead mileage, dead running, light running, empty cars or deadheading in public transport and empty leg in air charter is when a revenue-gaining vehicle operates without carrying or accepting passengers, such as when coming from a garage to begin its first trip of the day. Similar terms in the UK include empty coaching stock (ECS) move and dead in tow (DIT). The term ''deadheading (employee), deadheading'' or ''jumpseating'' also applies to the practice of allowing employees of a common carrier to travel in a vehicle as a non-revenue passenger. For example, an airline might assign a pilot living in New York to a flight from Denver to Los Angeles, and the pilot would simply catch any flight going to Denver, either wearing their uniform or showing ID, in lieu of buying a ticket. Also, some transport companies will allow employees to use the service when off duty, such as a city bus line allowing an off-duty driver to commute to and from work for free. Additionally, inspectors from ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Integer Programming
An integer programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers. In many settings the term refers to integer linear programming (ILP), in which the objective function and the constraints (other than the integer constraints) are linear. Integer programming is NP-complete. In particular, the special case of 0–1 integer linear programming, in which unknowns are binary, and only the restrictions must be satisfied, is one of Karp's 21 NP-complete problems. If some decision variables are not discrete, the problem is known as a mixed-integer programming problem. Canonical and standard form for ILPs In integer linear programming, the ''canonical form'' is distinct from the ''standard form''. An integer linear program in canonical form is expressed thus (note that it is the \mathbf vector which is to be decided): : \begin & \underset && \mathbf^\mathrm \mathbf\\ & \text && A \mathbf \le \mathbf ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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NP-hard
In computational complexity theory, a computational problem ''H'' is called NP-hard if, for every problem ''L'' which can be solved in non-deterministic polynomial-time, there is a polynomial-time reduction from ''L'' to ''H''. That is, assuming a solution for ''H'' takes 1 unit time, ''H''s solution can be used to solve ''L'' in polynomial time. As a consequence, finding a polynomial time algorithm to solve a single NP-hard problem would give polynomial time algorithms for all the problems in the complexity class NP. As it is suspected, but unproven, that P≠NP, it is unlikely that any polynomial-time algorithms for NP-hard problems exist. A simple example of an NP-hard problem is the subset sum problem. Informally, if ''H'' is NP-hard, then it is at least as difficult to solve as the problems in NP. However, the opposite direction is not true: some problems are undecidable, and therefore even more difficult to solve than all problems in NP, but they are probably not NP- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Pregolya
The Pregolya or Pregola (; ; ; ) is a river in the Russian Kaliningrad Oblast exclave. Name A possible ancient name by Ptolemy of the Pregolya River is Chronos (from Germanic *''hrauna'', "stony"), although other theories identify Chronos as a much larger river, the Nemunas. The oldest recorded names of the river are ''Prigora'' (1302), ''Pregor'' (1359), ''Pregoll, Pregel'' (1331), ''Pregill'' (1460). Georg Gerullis connected the name with Lithuanian ''prãgaras'', ''pragorė̃'' ("abyss") and the Lithuanian verb ''gérti'' ("drink"). Vytautas Mažiulis instead derived it from ''spragė́ti'' or ''sprógti'' ("burst") and the suffix -''ara'' ("river"). Overview It starts as a confluence of the Instruch and the Angrapa and drains into the Baltic Sea through the Vistula Lagoon. Its length under the name of Pregolya is 123 km, 292 km including the Angrapa. The basin has an area of 15,500 km2. The average flow is 90 m3/s. Euler's Seven Bridges of Königsberg pro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Kaliningrad
Kaliningrad,. known as Königsberg; ; . until 1946, is the largest city and administrative centre of Kaliningrad Oblast, an Enclave and exclave, exclave of Russia between Lithuania and Poland ( west of the bulk of Russia), located on the Pregolya, Pregolya River, at the head of the Vistula Lagoon, and the only Port#Warm-water port, ice-free Russian port on the Baltic Sea. Its population in 2020 was 489,359. Kaliningrad is the second-largest city in the Northwestern Federal District, after Saint Petersburg and the List of cities and towns around the Baltic Sea, seventh-largest city on the Baltic Sea. The city had been founded in 1255 on the site of the ancient Old Prussians, Old Prussian settlement ''Twangste'' by the Teutonic Knights during the Northern Crusades, and named ''Königsberg'' ("king's mountain") in honor of King Ottokar II of Bohemia. A Baltic port city, it successively became the capital of the State of the Teutonic Order, the Duchy of Prussia and the provinces of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Königsberg
Königsberg (; ; ; ; ; ; , ) is the historic Germany, German and Prussian name of the city now called Kaliningrad, Russia. The city was founded in 1255 on the site of the small Old Prussians, Old Prussian settlement ''Twangste'' by the Teutonic Knights during the Northern Crusades, Baltic Crusades. It was named in honour of King Ottokar II of Bohemia, who led a campaign against the pagan Old Prussians, a Baltic tribe. A Baltic Sea, Baltic port city, it successively became the capital of the State of the Teutonic Order, the Duchy of Prussia and the provinces of East Prussia and Province of Prussia, Prussia. Königsberg remained the coronation city of the Prussian monarchy from 1701 onwards, though the capital was Berlin. From the thirteenth to the twentieth centuries on, the inhabitants spoke predominantly German language, German, although the city also had a profound influence upon the Lithuanian and Polish cultures. It was a publishing center of Lutheranism, Lutheran literatu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Leonhard Euler
Leonhard Euler ( ; ; ; 15 April 170718 September 1783) was a Swiss polymath who was active as a mathematician, physicist, astronomer, logician, geographer, and engineer. He founded the studies of graph theory and topology and made influential discoveries in many other branches of mathematics, such as analytic number theory, complex analysis, and infinitesimal calculus. He also introduced much of modern mathematical terminology and Mathematical notation, notation, including the notion of a mathematical function. He is known for his work in mechanics, fluid dynamics, optics, astronomy, and music theory. Euler has been called a "universal genius" who "was fully equipped with almost unlimited powers of imagination, intellectual gifts and extraordinary memory". He spent most of his adult life in Saint Petersburg, Russia, and in Berlin, then the capital of Kingdom of Prussia, Prussia. Euler is credited for popularizing the Greek letter \pi (lowercase Pi (letter), pi) to denote Pi, th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Seven Bridges Of Königsberg
The Seven Bridges of Königsberg is a historically notable problem in mathematics. Its negative resolution by Leonhard Euler, in 1736, laid the foundations of graph theory and prefigured the idea of topology. The city of Königsberg in Prussia (now Kaliningrad, Russia) was set on both sides of the Pregel River, and included two large islands— Kneiphof and Lomse—which were connected to each other, and to the two mainland portions of the city, by seven bridges. The problem was to devise a walk through the city that would cross each of those bridges once and only once. By way of specifying the logical task unambiguously, solutions involving either # reaching an island or mainland bank other than via one of the bridges, or # accessing any bridge without crossing to its other end are explicitly unacceptable. Euler proved that the problem has no solution. The difficulty he faced was the development of a suitable technique of analysis, and of subsequent tests that established ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Lagrange Multiplier
In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function (mathematics), function subject to constraint (mathematics), equation constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variable (mathematics), variables). It is named after the mathematician Joseph-Louis Lagrange. Summary and rationale The basic idea is to convert a constrained problem into a form such that the derivative test of an unconstrained problem can still be applied. The relationship between the gradient of the function and gradients of the constraints rather naturally leads to a reformulation of the original problem, known as the Lagrangian function or Lagrangian. In the general case, the Lagrangian is defined as \mathcal(x, \lambda) \equiv f(x) + \langle \lambda, g(x)\rangle for functions f, g; the notation \langle \cdot, \cdot \rangle denotes an inner prod ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Convex Hull
In geometry, the convex hull, convex envelope or convex closure of a shape is the smallest convex set that contains it. The convex hull may be defined either as the intersection of all convex sets containing a given subset of a Euclidean space, or equivalently as the set of all convex combinations of points in the subset. For a Bounded set, bounded subset of the plane, the convex hull may be visualized as the shape enclosed by a rubber band stretched around the subset. Convex hulls of open sets are open, and convex hulls of compact sets are compact. Every compact convex set is the convex hull of its extreme points. The convex hull operator is an example of a closure operator, and every antimatroid can be represented by applying this closure operator to finite sets of points. The algorithmic problems of finding the convex hull of a finite set of points in the plane or other low-dimensional Euclidean spaces, and its projective duality, dual problem of intersecting Half-space (geome ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Convex Optimization
Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently, maximizing concave functions over convex sets). Many classes of convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard. Definition Abstract form A convex optimization problem is defined by two ingredients: * The ''objective function'', which is a real-valued convex function of ''n'' variables, f :\mathcal D \subseteq \mathbb^n \to \mathbb; * The ''feasible set'', which is a convex subset C\subseteq \mathbb^n. The goal of the problem is to find some \mathbf \in C attaining :\inf \. In general, there are three options regarding the existence of a solution: * If such a point ''x''* exists, it is referred to as an ''optimal point'' or ''solution''; the set of all optimal points is called the ''optimal set''; and the problem is called ''solvable''. * If f is unbou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |