Approximation algorithms for solving multi-objective optimization problems

This paper tries to cover the main aspects/properties related to scheduling problems, approximation algorithms, and multi-objective combinatorial optimization. Then, we try to describe the main techniques that can be used to solve such problems. In this paper, the reviews results relate to multi-objective optimization problems, exact and approximation search, with the aim of getting all Pareto optimal solutions for some NP-hard problems

Scheduling with time-of-use costs

We address a class of problems of scheduling a set of independent jobs onto a single machine that charges each job for its processing under variable time-of-use tariffs. Our scheduling objective is to minimize the total cost of processing all the jobs subject to a minimum level of performance in one of the regular scheduling criteria. For each of the problems in the class, we establish its computational tractability. For those that are tractable we provide an efficient algorithm, while for those that are intractable we provide a pseudo-polynomial-time algorithm or a polynomial-time approximation scheme