Approximation Algorithms: Good Solutions to Hard Problems
نویسندگان
چکیده
منابع مشابه
Approximation algorithms for NP-hard optimization problems
In this chapter, we discuss approximation algorithms for optimization problems. An optimization problem consists in finding the best (cheapest, heaviest, etc.) element in a large set P, called the feasible region and usually specified implicitly, where the quality of elements of the set are evaluated using a function f(x), the objective function, usually something fairly simple. The element tha...
متن کاملAn Analysis of Evolutionary Algorithms for Finding Approximation Solutions to Hard Optimisation Problems
In practice, evolutionary algorithms are often used to find good feasible solutions to complex optimisation problems in a reasonable running time, rather than the optimal solutions. In theory, an important question we should answer is that: how good approximation solutions can evolutionary algorithms produce in a polynomial time? This paper makes an initial discussion on this question and conne...
متن کاملLec . 1 : Approximation Algorithms for NP - hard problems
In this course, we will be studying, as the title suggests, the approximability and inapproximability (limits of approximability) of different combinatorial optimization problems. All the problems we will be looking at will be ones that lack efficient algorithms and in particular will be NP-hard problems. The last two-three decades has seen remarkable progress in approximation algorithms for se...
متن کاملBi-Factor Approximation Algorithms for Hard Capacitated k-Median Problems
In the classical k-median problem the goal is to select a subset of at most k facilities in order to minimize the total cost of opened facilities and established connections between clients and opened facilities. We consider the capacitated version of the problem, where a single facility may only serve a limited number of clients. We construct approximation algorithms slightly violating the cap...
متن کاملLec . 2 : Approximation Algorithms for NP - hard Problems ( Part II )
We will continue the survey of approximation algorithms in this lecture. First, we will discuss a (1+ε)-approximation algorithm for Knapsack in time poly(n, 1/ε). We will then see applications of some heavy hammers such as linear programming (LP) and semi-definite programming (SDP) towards approximation algorithms. More specifically, we will see LPbased approximation for MAXSAT and MAXCUT. In t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The American Mathematical Monthly
سال: 1995
ISSN: 0002-9890,1930-0972
DOI: 10.1080/00029890.1995.11990535