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It is well known that, under very weak assumptions, multiobjective optimization problems admit (1+ε,⋯,1+ε)-approximation sets (also called ε-Pareto sets ) of polynomial cardinality (in the size of the instance and in 1ε). While an approximation guarantee of 1+εfor any ε0is the best one...
Persistent link: https://www.econbiz.de/10015331781
We study the approximation of general multiobjective optimization problems with the help of scalarizations. Existing results state that multiobjective minimization problems can be approximated well by norm-based scalarizations. However, for multiobjective maximization problems, only...
Persistent link: https://www.econbiz.de/10015188355
We study the approximation of general multiobjective optimization problems with the help of scalarizations. Existing results state that multiobjective minimization problems can be approximated well by norm-based scalarizations. However, for multiobjective maximization problems, only...
Persistent link: https://www.econbiz.de/10015400935
We present extensions to the Online Delay Management Problem on a Single Train Line. While a train travels along the line, it learns at each station how many of the passengers wanting to board the train have a delay of δ. If the train does not wait for them, they get delayed even more since...
Persistent link: https://www.econbiz.de/10010999561
We consider the traveling tournament problem, which is a well-known benchmark problem in tournament timetabling. It consists of designing a schedule for a sports league of n teams such that the total traveling costs of the teams are minimized. The most important variant of the traveling...
Persistent link: https://www.econbiz.de/10010999722
In this article, we introduce the rectangular knapsack problem as a special case of the quadratic knapsack problem consisting in the maximization of the product of two separate knapsack profits subject to a cardinality constraint. We propose a polynomial time algorithm for this problem that...
Persistent link: https://www.econbiz.de/10014503814