The problem of minimizing the weighted sum of completion times when scheduling jobs on a single machine subject to precedence constraints is NP-hard, but can be solved in polynomial time for interesting families of constraints, such as series-parallel constraints and two-dimensional constraints. A classical decomposition theorem of Sydney leads to a simple polynomial-time algorithm for series-p...

In this paper we consider the labor constrained scheduling problem (LCSP), in which a set of jobs to be processed is subject to precedence and labor requirement constraints. Each job has a speciied processing time and a labor requirements proole, which typically varies as the job is processed. Given the amount of labor available at each period, the problem consists in determining starting times...

Constraint-based scheduling has become the dominant form of modeling and solving scheduling problems. Recently, due to ever more powerful embedded processors, it has become possible to embed and run constraint-based schedulers on-line even for fast processes such as product assembly sequencing. This makes constraint-based scheduling interesting to the control community as a new tool for system ...

Scheduling precedence constrained jobs on identical parallel machines is a well investigated problem with many applications. AND/OR-networks constitute a useful generalization of standard precedence constraints where certain jobs can be executed as soon as at least one of their direct predecessors is completed. For the problem of scheduling AND/OR-networks on parallel machines, we present a 2-a...

In this paper we present an approach to speciication and veriication of distributed hard real-time systems. By integrating RTL and precedence constraints, we combine the comprehensiveness of precedence graphs with the expressive power and proofability of RTL. Thus, our approach allows easy comprehension by the human designer and formal correctness. We propose to use a static scheduling algorith...

The integration of machine learning methods into meta-heuristic search techniques is currently an important topic in the field of combinatorial optimisation. It is often referred to as intelligent optimisation [1]. Learning has the potential of helping the search process in several ways. Searching for instance, can become more generic when online learning and automation mechanisms tune the crit...

This paper considers the problem of minimizing make-span and maximum tardiness simultaneously for scheduling jobs under non-identical job sizes, dynamic job arrivals, incompatible job families,and sequence-dependentfamily setup time on the single batch- processor, where split size of jobs is allowed between batches. At first, a new Mixed Integer Linear Programming (MILP) model is proposed for t...

Assembly lines are flow-oriented production systems that are of great importance in the industrial production of standard, high-volume products and even more recently, they have become commonplace in producing low-volume custom products. The main goal of designers of these lines is to increase the efficiency of the system and therefore, the assembly line balancing to achieve an optimal system i...

A parallel computational model is defined which addresses I/O contention, latency, and pipe-lined message passing between tasks allocated to different processors. The model can be used for parallel task-allocation on either a network of workstations or on a multi-stage inter-connected parallel machine. To study performance bounds more closely, basic properties are developed for when the precede...