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The basic idea of the Variable Neighborhood Search (VNS) algorithm is to systematically explore the neighborhood of current solution using a set of predefined neighborhood structures. Since different problem instances have different landscape and complexity, the choice of which neighborhood structure to be applied is a challenging task. Different neighborhood structures may lead to different solution...
Inspired by the competition of sport teams in a sport league, an algorithm is presented for optimizing nonlinear continuous functions. A number of individuals as sport teams compete in an artificial league for several weeks (iterations). Based on the league schedule in each week, teams play in pairs and the outcome is determined in terms of win or loss, given known the team's playing strength (fitness...
Grid workflow schedule requires sophisticated expertise of domain in order to automate the process of managing workflows and its components. QoS-aware selection and execution of grid workflow can fulfill customer's expectations, a new preference method is proposed to design the grid workflow schedule. The grid workflow matching relation is achieved by mobile agent negotiation based on projection-join...
Efficient task scheduling, as a crucial step to achieve high performance for multiprocessor platform, remains one of the challenge problems despite of numerous studies. This paper presents a novel scheduling algorithm based on Bayesian optimization algorithm (BOA) for heterogeneous computing environment. In the proposed algorithm, BOA constructs and updates Bayesian network according to the task graph...
Aviation project which always involves too many resources need to do resource leveling for enhancing the utilization of resources so as to reducing project cost. Intelligent optimization algorithms and heuristic approaches are inefficient and inflexible when solving large-scale aviation resource leveling problems. A hybrid algorithm based on Artificial Immune Algorithm (AIA) and Ant Colony Optimization...
Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems and it is also an appealing NP-complete problem. There is a number of heuristic and meta-heuristic algorithms that were tailored to deal with scheduling of independent jobs. In this paper we investigate the efficiency of differential evolution on the scheduling problem.
This paper presents an algorithm that is based on ant system to solve the course timetabling problem. The problem is modeled using the bipartite graph. Four heuristic factors are derived from the graph characteristic, are used to direct ants as the agent in finding course timetable elements. The concept of negative pheromone was also applied to ensure that paths leading to dead ends are not chosen...
Scheduling for the flexible job-shop is very important in both fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. Particle swarm...
Asset assignment and scheduling algorithms were developed and implemented to support a team-in-the-loop planning experiment conducted at the Naval Postgraduate School (NPS) in March 2009. The experiment examined planning and information flows among three cells in an abstracted and simplified Maritime Operations Center (MOC). This paper describes two optimization-based modules that focused on the Future...
Task scheduling is one of the core steps to effectively exploit the capabilities of distributed heterogeneous computing systems. In this paper, a novel discrete differential evolution (DDE) algorithm is presented to address the task scheduling problem. The encoding schemes and the adaptation of classical differential evolution algorithm for dealing with discrete variables are discussed as well as...
This paper improves integer coded genetic algorithm (ICGA) with some operators, to schedule the commitment states of units. ICGA technique reduces the size of chromosomes and computation time significantly. Chromosomes contain sequence of alternative sign integers which represent operation/reservation hours of the generating units. Therefore minimum up/down time can be checked directly in chromosome...
We describe a system for scheduling a conference based on incomplete information about available resources and scheduling constraints. We explain the representation of uncertain knowledge and related common-sense rules, which allow reasoning based on uncertain and partially missing data.
In this paper, we address a new integration of column generation and Lagrangian relaxation for solving flowshop scheduling problems to minimize the total weighted tardiness. In the proposed method, initial columns are generated by using near-optimal dual solution using the Lagrange multipliers derived by Lagrangian relaxation method. After the generation of base columns, the column generation is executed...
Timber harvest planning deals with selecting a forest area to harvest in a particular time period take into consideration both economic and environmental issues. The problem has been modelled using unit restriction approach and area restriction approach. An optimal or a feasible harvest schedules subject to adjacency constraints is generated using exact methods or meta-heuristic optimization techniques...
In this paper, we combine graph coloring heuristics, namely largest degree and saturation degree with the concept of a heuristic modifier under the framework of squeaky wheel optimization for solving a set of examination timetabling problems. Both components interact adaptively to determine the best ordering of examinations to be processed at each iteration. A variety of approaches using different...
The implementation and optimization of collective communication operations is an important field of active research. Such operations directly influence application performance and need to map the communication requirements in an optimal way to steadily changing network architectures. In this work, we define an abstract domain-specific language to express arbitrary group communication operations. We...
This work treats the topic of solving dynamic pickup and delivery problems, also known as dial-a-ride problems. A simulation model is introduced that describes how an agent is able to satisfy the transportation requests. The agent behavior is given in form of a complex dispatching rule, which is optimized by metaheuristic approaches. For this purpose, a fitness function is described which is used...
In this paper, we perform a computational study of lower bounding schemes for job shop scheduling problems under special consideration of total weighted tardiness costs. Due to the characteristics of this objective function, lower bounds are much more difficult to derive than for the classical makespan. On the other hand, the practical relevance of tardiness related costs makes it even more important...
We introduce the problem of joint routing, scheduling and power control for multiple information flows in half-duplex, interference limited ad-hoc networks. The joint problem of optimizing for throughput is NP-Hard, and so we present an approximation of the problem and a general framework for solving it in O(N3) time. We attack the problem in two ways, first by presenting a reformulation and decomposition...
Nurse scheduling problem (NSP) is the problem of determining a reasonable and efficient work schedule for nurses. This paper presents a new external memory-based approach along with Multi-Objective Genetic Algorithms (MOGA) to solve multiobjective NSPs. In multiobjective modeling of NSPs, there are several objectives which are in conflict with each other, and there are some hard constraints that should...
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