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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 schoo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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'' also applies to the practice of allowing employees of a common carrier to use 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, free. Additionally, inspectors from a regulatory agency may use transport on a dead ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Integer Programming
An integer programming problem is a mathematical optimization or Constraint satisfaction problem, 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 function (calculus), 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 & \text && \math ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NP-hard
In computational complexity theory, NP-hardness ( non-deterministic polynomial-time hardness) is the defining property of a class of problems that are informally "at least as hard as the hardest problems in NP". A simple example of an NP-hard problem is the subset sum problem. A more precise specification is: a problem ''H'' is NP-hard when every problem ''L'' in NP can be reduced in polynomial time 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 any NP-hard problem would give polynomial time algorithms for all the problems in NP. As it is suspected that P≠NP, it is unlikely that such an algorithm exists. It is suspected that there are no polynomial-time algorithms for NP-hard problems, but that has not been proven. Moreover, the class P, in which all problems can be solved in polynomial time, is contained in the NP class. Defi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pregolya
The Pregolya or Pregola (russian: Прего́ля; german: Pregel; lt, Prieglius; pl, Pregoła) 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").http://journals.lki.lt/actalinguisticalithuanica/article/download/856/947/ 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 k ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kaliningrad
Kaliningrad ( ; rus, Калининград, p=kəlʲɪnʲɪnˈɡrat, links=y), until 1946 known as Königsberg (; rus, Кёнигсберг, Kyonigsberg, ˈkʲɵnʲɪɡzbɛrk; rus, Короле́вец, Korolevets), is the largest city and administrative centre of Kaliningrad Oblast, a Russian semi-exclave between Lithuania and Poland. The city sits about west from mainland Russia. The city is situated on the Pregolya River, at the head of the Vistula Lagoon on the Baltic Sea, and is the only ice-free port of Russia and the Baltic states on the Baltic Sea. Its population in 2020 was 489,359, with up to 800,000 residents in the urban agglomeration. Kaliningrad is the second-largest city in the Northwestern Federal District, after Saint Petersburg, the third-largest city in the Baltic region, and the seventh-largest city on the Baltic Sea. The settlement of modern-day Kaliningrad was founded in 1255 on the site of the ancient Old Prussian settlement ''Twangste'' by th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Königsberg
Königsberg (, ) was the historic Prussian city that is now Kaliningrad, Russia. Königsberg was founded in 1255 on the site of the ancient Old Prussian settlement ''Twangste'' by the Teutonic Knights during the Northern Crusades, and was named in honour of King Ottokar II of Bohemia. A Baltic port city, it successively became the capital of the Królewiec Voivodeship, the State of the Teutonic Order, the Duchy of Prussia and the provinces of East Prussia and Prussia. Königsberg remained the coronation city of the Prussian monarchy, though the capital was moved to Berlin in 1701. Between the thirteenth and the twentieth centuries, the inhabitants spoke predominantly German, but the multicultural city also had a profound influence upon the Lithuanian and Polish cultures. The city was a publishing center of Lutheran literature, including the first Polish translation of the New Testament, printed in the city in 1551, the first book in Lithuanian and the first Lutheran catechism, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Leonhard Euler
Leonhard Euler ( , ; 15 April 170718 September 1783) was a Swiss mathematician, physicist, astronomer, geographer, logician and engineer who founded the studies of graph theory and topology and made pioneering and influential discoveries in many other branches of mathematics such as analytic number theory, complex analysis, and infinitesimal calculus. He introduced much of modern mathematical terminology and notation, including the notion of a mathematical function. He is also known for his work in mechanics, fluid dynamics, optics, astronomy and music theory. Euler is held to be one of the greatest mathematicians in history and the greatest of the 18th century. A statement attributed to Pierre-Simon Laplace expresses Euler's influence on mathematics: "Read Euler, read Euler, he is the master of us all." Carl Friedrich Gauss remarked: "The study of Euler's works will remain the best school for the different fields of mathematics, and nothing else can replace it." Euler is a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 this ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dynamic Programming
Dynamic programming is both a mathematical optimization method and a computer programming method. The method was developed by Richard Bellman in the 1950s and has found applications in numerous fields, from aerospace engineering to economics. In both contexts it refers to simplifying a complicated problem by breaking it down into simpler sub-problems in a recursive manner. While some decision problems cannot be taken apart this way, decisions that span several points in time do often break apart recursively. Likewise, in computer science, if a problem can be solved optimally by breaking it into sub-problems and then recursively finding the optimal solutions to the sub-problems, then it is said to have ''optimal substructure''. If sub-problems can be nested recursively inside larger problems, so that dynamic programming methods are applicable, then there is a relation between the value of the larger problem and the values of the sub-problems.Cormen, T. H.; Leiserson, C. E.; Rives ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lagrange Multiplier
In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function subject to equality constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variables). It is named after the mathematician Joseph-Louis Lagrange. 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. The method can be summarized as follows: in order to find the maximum or minimum of a function f(x) subjected to the equality constraint g(x) = 0, form the Lagrangian function :\mathcal(x, \lambda) = f(x) + \lambda g(x) and find the stationary points of \mathcal considered as a function of x and the Lagrange mu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Convex Hull
In geometry, the convex hull or 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 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 dual problem of intersecting half-spaces, are fundamental problems of com ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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. Convex optimization has applications in a wide range of disciplines, such as automatic control systems, estimation and signal processing, communications and networks, electronic circuit design, data analysis and modeling, finance, statistics ( optimal experimental design), and structural optimization, where the approximation concept has proven to be efficient. With recent advancements in computing and optimization algorithms, convex programming is nearly as straightforward as linear programming. Definition A convex optimization problem is an optimization problem in which the objective function is a convex function and the feasible set is a c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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