In classical deterministic scheduling problems, it is assumed that all jobs have to be
processed. However, in many practical cases, mostly in highly loaded make-to-order …

Algorithms for approximating the nondominated set of multiobjective optimization problems
are reviewed. The approaches are categorized into general methods that are applicable …

With pervasive applications of new information technology, a larger number of
manufacturing big data is generated. This paper considers the unrelated parallel scheduling …

We consider the problem of covering and packing subsets of δ-hyperbolic metric spaces and
graphs by balls. These spaces, defined via a combinatorial Gromov condition, have recently …

This paper describes a novel architecture of fault tolerant solid state mass memory (SSMM)
for satellite applications. Mass memories with low-latency time, high throughput, and storage …

We investigate the problem of computing a minimum set of solutions that approximates
within a specified accuracy ϵ the Pareto curve of a multiobjective optimization problem. We …

This research proposes two heuristics and a Genetic Algorithm (GA) to find non-dominated
solutions to multiple-objective unrelated parallel machine scheduling problems. Three …

We consider a version of parallel machine scheduling with rejection. An instance of the
problem is given by m identical parallel machines and a set of n independent jobs, with each …

Applications implemented on critical systems are subject to both safety critical and real-time
constraints. Classically, applications are specified as precedence task graphs that must be …

Motivated by current green manufacturing standards, in this paper we study a parallel-
machine scheduling model in which the energy cost incurred on each machine is machine …