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This paper gives overview of two modern approaches to enterprise resources scheduling problem: continuous time problem setting that leads to a combinatorial set of classical linear programming models and discrete time approach that gives an integer programming model. We follow the main steps of problem formulating and find decision points where the researcher chooses which model and computational...
We study approximation algorithms for scheduling problems with the objective of minimizing total weighted completion time, under identical and related machine models with job precedence constraints. We give algorithms that improve upon many previous 15 to 20-year-old state-of-art results. A major theme in these results is the use of time-indexed linear programming relaxations. These are natural relaxations...
Considering the low efficiency and lack of intelligent dispatching decision of the agricultural machinery scheduling problem, an improved Immune-Tabu Search Algorithm (ITSA) based on the immune optimization algorithm is proposed. A new operator, named TSA, is designed through improvement on the generation of neighborhood solution based on the tabu search algorithm. At the beginning of the iterations,...
Imprecise input data imposes special challenges to workflow scheduling. This paper introduces a robust scheduler based on particle swarm optimisation, called RobWE, which considers uncertainties of available bandwidth when producing schedules for workflow ensembles. The proposed scheduler is also a flexible scheduler since it allows the replacement of its objective function according to the user's...
Erasure-coded storage systems have gained considerable adoption recently since they can provide the same level of reliability with significantly lower storage overhead compared to replicated systems. However, background traffic of such systems - e.g. repair, rebalance, backup and recovery traffic - often has large volume and consumes significant network resources. Independently scheduling such tasks...
With the frequent occurrence of large-scale disasters, such as landslide and earthquake, timely and effective emergency resource scheduling becomes more and more important. Lots of disasters need multi-period rescue to satisfy the demand of disaster areas. In order to find a better plan to achieve the multi-period disaster relief, in this paper, a multi-period emergency resource scheduling problem...
The pressure to maintain (or increase) the level of competitiveness in companies leads to an ever-increasing requirement for effective management supported by the variety of existing resources, which tend to interfere into the work of the manager. Particularly, in the case of waiting queues, the most relevant aspect is the combination of the number of multitasking servers assigned to attend and the...
This article presents a new model and a resolution algorithm, based on Tabu Search, for the assignment of Virtual Machines (VMs) to servers in a data center. We propose a Mixed Integer Programming (MIP) model that optimizes the Quality of Service (QoS) and power consumption of applications, taking into account their communication traffic and dynamic aspects. A hierarchic method and a Tabu Search heuristic...
In a hydro-dominated power system, with complex inter-temporal linkages, capacities of individual projects and project configurations are more complicated than using the simple megawattage, often used to denote capacity in thermally dominated systems. In this paper, the long term hydro scheduling problem is solved and used to test novel definitions of hydro-capacities, based on expected cost and cost...
With Docker gaining widespread popularity in the recent years, the container scheduler becomes a crucial role for the exploding containerized applications and services. In this work, the container host energy conservation, the container image pulling costs from the image registry to the container hosts and the workload network transition costs from the clients to the container hosts are evaluated...
A general model on single-machine scheduling problems with past-sequence-dependent delivery times is developed in this paper, where the actual processing time of a job is defined by a function of its position in a schedule. Moreover, position-dependent effects in both processing times and delivery times are considered simultaneously. Problems with completion time related criteria are presented and...
Nurses planning is a challenging and a complex task that arises daily within healthcare facilities. Establishing rosters that meet both hospital requirements and nurses' preferences takes a considerable time and cannot be done manually. The equitable distribution of workload is one of the major factors contributing to nurses' satisfaction and, eventually, the quality of care delivered. However, the...
Scheduling is a core component within distributed systems to determine optimal allocation of tasks within servers. This is challenging within modern Cloud computing systems – comprising millions of tasks executing in thousands of heterogeneous servers. Theoretical scheduling is capable of providing complete and sophisticated algorithms towards a single objective function. However, Cloud computing...
In this paper, we propose a flexible workflow scheduler that facilitates the replacement of the objective function according to the user's needs. The possibility of replacing the objective function extends the usability of the scheduler for a variety of objectives. The proposed flexible scheduler uses Particle Swarm Optimization (PSO) to assist the production of schedules on cloud resources. We perform...
This paper considers a two-stage hybrid flowshop problem where there are a single batch processing machine and a single machine. Each job with release time is assigned into some batches. The waiting time between the batch processing machine and the single machine is limited to make the problem more practical. A MIP model is developed to describe the proposed problem. Since the problem is NP-hard,...
This study addresses the efficiency of multiple threads Tabu search (TS) in solving scheduling problems. Nowadays, most desktop personal computers equip with multicore CPU. It is possible to achieve parallel searching strategy on a desktop computer. A problem of scheduling, which minimizes the total tardiness of a set of jobs to be scheduled on parallel identical machines, is presented as an example...
Most existing studies on production scheduling considered only one resource type, usually the machines. But in certain actual manufacturing environments, other resources, such as tools, operators, and so on, may become a scare resource for the short term production scheduling. Therefore, this study investigates the scheduling problem that simultaneously considers machines and their auxiliary tools...
Since the 2010 version, the Solver Add-in of Microsoft Excel comprises the so-called Evolutionary Solver. The application of this Solver to a combinatorial optimization problem requires a spreadsheet which determines the objective function value corresponding to given values for the decision variables. This paper refers to the resource-constrained project-scheduling problem; we study how to implement...
There is an interest in search algorithms capable of learning and adapting their behaviour while solving a given problem. A hyper-heuristic operates on a set of predefined heuristics and applies a machine learning technique to predict which heuristic is the most effective to apply at a given point in time. Thompson Sampling is a machine learning mechanism interacting with the search environment to...
Task scheduling in data centers is a complex task due to their evolution in size, complexity, and performance. At the same time, customers’ requirements have become more sophisticated in terms of execution time and throughput. Against this background, this work presents a new model of resource allocation that optimizes task scheduling using a multi-objective optimization (MOO) and particle swarm optimization...
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