Spelling suggestions: "subject:"cheduling -- amathematical models."" "subject:"cheduling -- dmathematical models.""
41 |
Scheduling system of affine recurrence equations by means of piecewise affine timing functionsMui, Lap K. 05 March 1992 (has links)
Many systematic methods exist for mapping algorithms to processor arrays. The
algorithm is usually specified as a set of recurrence equations, and the processor arrays
are synthesized by finding timing and allocation functions which transform index points
in the recurrences into points in a space-time domain.
The problem of scheduling (i.e. finding the timing function) of recurrence equations
has been studied by a number of researchers. Of particular interest here are Systems of
Affine Recurrence Equations (SAREs). The existing methods are limited to affine (or
linear) schedules over the entire domain of computation. For some algorithms, there are
points in the computation domain where the dependencies point in opposite directions,
and an affine schedule does not exist, although a valid Piecewise Affine Schedule (PAS)
can exist. The objective of this thesis is to examine these schedules and obtain a
systematic method for deriving such schedules for SAREs. PAS can be found by first
partitioning the computation domain and then obtaining a new SARE by renaming the
variables. By partitioning the computation domain, we can obtain additional parallelism
from the dependency graph, and find faster schedules over subspaces of the domain. In
this paper, we describe a procedure for partitioning the domain and to generate a new
SARE by renaming the variables. Some heuristics are introduced for partitioning the
domain based on the properties of dependence vectors. After the partitioning and
renaming, an existing method (due to Mauras et al.) is applied to find the schedules.
Examples of Toeplitz System and Algebraic Path Problem are used to illustrate the results. / Graduation date: 1992
|
42 |
An enhanced ant colony optimization approach for integrating process planning and scheduling based on multi-agent systemZhang, Sicheng., 张思成. January 2012 (has links)
Process planning and scheduling are two important manufacturing planning functions which are traditionally performed separately and sequentially. Usually, the process plan has to be prepared first before scheduling can be performed. However, due to the complexity of manufacturing systems and the uncertainties and dynamical changes encountered in practical production, process plans and schedules may easily become inefficient or even infeasible. The concept of integrated process planning and scheduling (IPPS) has been proposed to improve the efficiency, effectiveness as well as flexibility of the respective process plan and schedule. By combining both functions together, the process plan for producing a part could be dynamically arranged in accordance with the availability of manufacturing resources and current status of the system, and its operations’ schedule could be determined concurrently. Therefore, IPPS could provide an essential solution to the dynamic process planning and scheduling problem in the practical manufacturing environment. Nevertheless, process planning and scheduling are both complex functions that depend on many factors and flexibilities in the manufacturing system, IPPS is therefore a highly complex NP-hard problem.
Ant colony optimization (ACO) is a widely applied meta-heuristics, which has been proved capable of generating feasible solutions for IPPS problem in previous research. However, due to the nature of the ACO algorithm, the performance is not that favourable compared with other heuristics. This thesis presents an enhanced ACO approach for IPPS. The weaknesses and limitations of standard ACO algorithm are identified and corresponding modifications are proposed to deal with the drawbacks and improve the performance of the algorithm. The mechanism is implemented on a specifically designed multi-agent system (MAS) framework in which ants are assigned as software agents to generate solutions. First of all, the manufacturing processes of the parts are graphically formulated as a disjunctive AND/OR graph. In applying the ACO algorithm, ants are deployed to find a path on the disjunctive graph. Such an ant route indicates a corresponding solution with associated operations scheduled by the sequence of ant visit.
The ACO in this thesis is enhanced with the novel node selection heuristic and pheromone update strategy. With the node selection heuristic, pheromone is deposited on the nodes as well as edges on the ant path. This is contrast to the conventional ACO algorithm that pheromone is only deposited on edges. In addition, a more reasonable strategy based on “earliest completion time” of operations are used to determine the heuristic desirability of ants, instead of the “greedy” strategy used in standard ACO, which is based on the “shortest processing time”.
The approach is evaluated by a comprehensive set of problems with a full set of flexibilities, while multiple performance measurements are considered, including makespan, mean flow time, average machine utilization and CPU time, among which makespan is the major criterion. The results are compared with other approaches and encouraging improvements on solution quality could be observed. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy
|
43 |
A column generation approach for stochastic optimization problemsWang, Yong Min 28 August 2008 (has links)
Not available / text
|
44 |
Scheduling trucks in port container terminals by a genetic algorithmZhang, Yuxuan, 張宇軒 January 2005 (has links)
published_or_final_version / abstract / Industrial and Manufacturing Systems Engineering / Master / Master of Philosophy
|
45 |
Crew scheduling and rostering for airport baggage services: optimization modellingYuen, Sau-yee, Christina., 阮秀儀. January 2000 (has links)
published_or_final_version / Mathematics / Master / Master of Philosophy
|
46 |
Non-linear integer programming fleet assignment modelPhokomela, Prince Lerato January 2016 (has links)
A dissertation submitted to the Faculty of Engineering and
the Built Environment, University of the Witwatersrand,
Johannesburg, in fulfilment of the requirements for the
degree of Master of Science in Engineering.
University of the Witwatersrand, Johannesburg, 2016 / Given a flight schedule with fixed departure times and cost, solving the fleet
assignment problem assists airlines to find the minimum cost or maximum
revenue assignment of aircraft types to flights. The result is that each flight is
covered exactly once by an aircraft and the assignment can be flown using the
available number of aircraft of each fleet type.
This research proposes a novel, non-linear integer programming fleet assignment
model which differs from the linear time-space multi-commodity network
fleet assignment model which is commonly used in industry. The performance
of the proposed model with respect to the amount of time it takes to create a
flight schedule is measured. Similarly, the performance of the time-space multicommodity
fleet assignment model is also measured. The objective function
from both mathematical models is then compared and results reported.
Due to the non-linearity of the proposed model, a genetic algorithm (GA)
is used to find a solution. The time taken by the GA is slow. The objective
function value, however, is the same as that obtained using the time-space
multi-commodity network flow model.
The proposed mathematical model has advantages in that the solution is
easier to interpret. It also simultaneously solves fleet assignment as well as
individual aircraft routing. The result may therefore aid in integrating more
airline planning decisions such as maintenance routing. / MT2017
|
47 |
Using Fuzzy Mathematical Models for construction project scheduling with time, cost and material restrictionsGonzalez, Julian Santiago, Sr. 12 July 2007 (has links)
No description available.
|
48 |
Modeling and analysis of scheduling restaurant personnelWade, Richard Barry 04 March 2009 (has links)
Scheduling workers in a restaurant is a difficult and time consuming task that involves matching the needs of the restaurant with respect to filling various shifts for different positions, the varying availabilities of the workers, along with their seniority levels and qualifications, among other factors. The restaurant manager/scheduler must adhere to these individual workers' restrictions, while at the same time satisfy the restaurant's needs. Another issue that a manager tries to accommodate is to equitably assign shifts to workers, attempting to balance their expressed wishes with their relative merits and qualifications; although in practice, this goal is rarely achieved. In this thesis, a mathematical model is developed to solve the scheduling problem, with attention focused on maximizing worker satisfaction levels, considering their seniority levels and their qualifications, while meeting with the restaurant's needs of filling various required shifts for various positions with capable workers. We show that this model possesses a hidden network structure that can be revealed via some simple variable substitutions. Consequently, an efficient network-flow approach can be used to solve the model and derive an optimal (integer) solution. We illustrate the model and the proposed algorithmic approach by generating a schedule using real data obtained via specially designed surveys from the Cheddar's restaurant in Newport News, Virginia. Further results on a variety of test problems are used to evaluate the performance of the algorithm, and suitable pre- and post-processor considerations are addressed to permit the use of this technology in a productive environment. / Master of Science
|
49 |
Design and implementation of an integrated algorithm for the vehicle routing problem with multiple constraintsMoolman, A.J. (Alwyn Jakobus) 27 May 2005 (has links)
Please read the abstract in the section 00front of this document / Dissertation (MSc (Industrial Systems))--University of Pretoria, 2006. / Industrial and Systems Engineering / unrestricted
|
50 |
Heuristic algorithm for multistage scheduling in food processing industryJuwono, Cynthia P. 16 March 1992 (has links)
A multistage production system consists of a number of
production stages that are interrelated, that is the output
from one stage forms input to the next stage. There are
constraints associated with each stage as well as constraints
imposed by the overall system. Besides, there are multiple
objectives that need to be satisfied, and in numerous cases,
these objectives conflict with each other. What is required is
an efficient technique to allocate and schedule resources so
as to provide a balance between the conflicting objectives
within the system constraints.
This study is concerned with the problem of scheduling
multistage production systems in food processing industry. The
system and products have complex structure and relationships.
This makes the system difficult to be solved analytically.
Therefore, the problem is solved by developing a heuristic
algorithm that considers most of the constraints. The output
generated by the algorithm includes a production schedule
which specifies the starting and completion times of the
products in each stage and the machines where the products are
to be processed. In addition, a summary of system performances
including throughput times, resources' utilizations, and tardy
products is reported. / Graduation date: 1992
|
Page generated in 0.108 seconds