Heuristic best-first search techniques have recently enjoyed ever-increasing scalability in finding satisficing solutions to a variety of automated planning problems, and temporal planning is no different. Unfortunately, achieving efficient computational performance often comes at the price of clear guidance toward solution of high quality. This fact is sharp in the case of many best-first sear...

The PEGS (Production and Environmental Generic Scheduler) program is a new generic scheduling program for manufacturing companies. It includes sort and search algorithms and can operate on the basis of elapsed time or economic values. Program performance is compared to a series of published benchmarks. The case study presented here illustrates the use of PEGS for a flow shop configuration at a ...

Batch processing is becoming more important in the process industries, because of the increasing product variety and the decreasing demand volumes for individual products. In batch process industries it is difficult to estimate the completion time, or makespan, of a set of jobs, because jobs interact at the shop floor. We assume a situation with hierarchical production control consisting of a p...

Suppose that a set of weighted tasks shall be assigned to a set of machines with possibly different speeds such that the load is distributed evenly among the machines. In computer science, this problem is traditionally treated as an optimization problem. One of the classical objectives is to minimize the makespan, i.e., the maximum load over all machines. Here we study a natural game theoretic ...

This paper presents an MILP model for the permutation flowshop wherein the setup times are both separable from the job processing times and independent of a job’s position in the processing sequence. Two experiments were conducted to estimate the computer times necessary to solve problems with up to 9 machines and 15 jobs, and to then compare these solution time requirements to those required ...

We have a set J of n jobs, and a set M of m machines. The processing time of job i is pij on machine j. Let f : J ←M be a function that assigns each job to exactly one machine. The makespan of f is max1≤j≤m ∑ i:f(i)=j pij , where ∑ i:f(i)=j pij is the total processing time of the jobs that are assigned to machine j. In the Scheduling on Unrelated Parallel Machines problem, the goal is to find a...

The most common objective function of task scheduling problems is makespan. However, on a computational grid, the 2nd optimal makespan may be much longer than the optimal makespan because the computing power of a grid varies over time. So, if the performance measure is makespan, there is no approximation algorithm in general for scheduling onto a grid. In this paper, a novel criterion of a sche...

Heterogeneous computing (HC) systems composed of interconnected machines with varied computational capabilities often operate in environments where there may be inaccuracies in the estimation of task execution times. Makespan (defined as the completion time for an entire set of tasks) is often the performance feature that needs to be optimized in such systems. Resource allocation is typically p...

Scheduling in Computational Grid (CG) is an important but complex task. It is done to schedule the submitted jobs onto the nodes of the grid so that some characteristic parameter is optimized. Makespan of the job is an important parameter and most often scheduling is done to optimize makespan. Genetic Algorithm (GA) is a search procedure based on the evolutionary technique that is able to solve...

We schedule the jobs from two agents on a single parallel-batching machine with equal processing time and non-identical job sizes. The objective is to minimize the makespan of the first agent subject to an upper bound on the makespan of the other agent. We show that there is no polynomial-time approximation algorithm for solving this problem with a finite worst-case ratio, unless P = NP. Then, ...