We consider the distributed scheduling problem on parallel machines with central objective of maximizing number on-time jobs. Jobs are self-interested utility-maximizers that can choose they processed and exclusively interested in reducing their own private function. Each machine processes jobs according to a local policy. discuss Nash equilibria resulting schedules perform thorough analysis (a...

When a computer system schedules jobs there is typically significant cost associated with preempting job during execution. This can be incurred from the expensive task of saving memory’s state or loading data into and out memory. Thus, it desirable to schedule non-preemptively avoid costs preemption. There need for non-preemptive schedulers desktops, servers, centers. Despite this need, gap bet...

In this work we study the unrelated parallel machines problem with the objective of the minimization of the maximum completion time or makespan (Cmax). We propose some metaheuristics based on a size-reduction of the original assignment problem. The idea is to consider only a few of the best possible machine assignments for the jobs and not all of them. We test the proposed simple algorithms wit...

Setup operations on machines usually need of tooling and/or personnel to be carried out. Therefore, the length of the setup might not only depend on the machine and job sequence, but also on the number of resources assigned. This situation is common in real problems arising in several industries where setup operations in production lines are frequent. These operations are indeed setups whose le...

This paper considers a flexible flow shop scheduling problem, where at least one production stage is made up of unrelated parallel machines. Moreover, sequenceand machinedependent setup times are given. The objective is to find a schedule that minimizes a positively weighted convex sum of makespan and the number of tardy jobs in a static flexible flow shop environment. For this problem, a 0-1 m...

The flexible flowshop problem is a well known and common challenge. Extended with unrelated parallel machines and especially with the dynamic aspect of distributed release times, the problem gets very ‘close to reality’. Triggered by the growing complexity of logistic systems, the paradigm of central planning is being shifted to decentralised control. As part of this, an autonomous control conc...

We investigate a difficult scheduling problem in a semiconductor manufacturing process that seeks to minimize the number of tardy jobs and makespan with sequence-dependent setup time, release time, due dates and tool constraints. We propose a mixed integer programming (MIP) formulation which treats tardy jobs as soft constraints so that our objective seeks the minimum weighted sum of makespan a...

Each of n jobs is to be processed without interruption on one of m unrelated parallel machines. The objective is to minimize the maximum completion time. A heuristic method is presented, the first stage of which uses linear programming to form a partial schedule leaving at most m 1 jobs unscheduled: the second stage schedules these m1 jobs using an enumerative method. For m 2 3, it is shown tha...

This paper addresses a scheduling problem with unrelated parallel machines, sequence dependent setups and due dates. The problem is based on a real case and the objective is to minimise the sum of the makespan and the weighted delays. A mixed integer linear programming model is proposed and since the model considers realistic constraints, a metaheuristic based on GRASP is used as a solution met...

Job scheduling has always been a challenging task in modern manufacturing and the most real life scheduling problems which involves multi-criteria and multi-machine environments. In this research our direction is largely motivated by the adoption of the Just-In-Time (JIT) philosophy in parallel machines system, where processing times of jobs are controllable. The goal of this paper is to minimi...