Optimization (Mathematics)

A non-monotonic method for large-scale nonnegative least squares

by Suvrit Sra

Matheuristics for Traffic Counter Location

by Antonio Bolufé

Matheuristics: Optimization, Simulation and Control

by Antonio Bolufé

A Decision Support System for Corporate Planning in a New Zealand Dairy Company

by Peter Mellalieu

Mellalieu, P. J. (1983). A Decision Support System for Corporate Planning in a New Zealand Dairy Company. Presented at the 25th Annual Conference of the Operational Research Society, Warwick University.

The context for the need to construct an interactive model of a large New Zealand dairy company is described. The... more The context for the need to construct an interactive model of a large New Zealand dairy company is described. The practical aspects of developing the hardware and software necessary for the decision support task are discussed followed by application examples. Comments are made regarding the combination of human judgement skills and mathematical models. Finally, some future developments of the NETPLAN system are outlined.

See also:
Mellalieu, P. J. (1982). A Decision Support System for Corporate Planning in the New Zealand Dairy Industry (Doctor of Philosophy in mathematics, statistics and operations research). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/568


Mellalieu, P. J., & Hall, K. R. (1983). An Interactive Planning Model for the New Zealand Dairy Industry. Journal of the Operational Research Society, 34, 521–532. doi:10.1057/jors.1983.119

Kearney, T. D., Hall, K. R., & Mellalieu, P. J. (1984). Recent Advances in Network Optimization Methods and Applications. Proceedings of the Annual Conference of the United Kingdom Operational Research Society. Presented at the Annual Conference of the United Kingdom Operational Research Society. Retrieved from http://unitec.academia.edu/PeterMellalieu/Papers/1569500/Recent_Advances_in_Network_Optimization_Methods_and_Applications

Towards decision support systems in New Zealand

by Peter Mellalieu

Mellalieu, P. J., & Houlistan, M. (1982). Towards decision support systems in New Zealand. Proceedings of the Operations Research Society of New Zealand (ORSNZ), 99–106. Retrieved from http://unitec.academia.edu/PeterMellalieu/Papers/1571355/Towards_decision_support_systems_in_New_Zealand

Related papers:
Mellalieu, P. J. (1982). A Decision Support System for Corporate Planning in the New Zealand Dairy Industry (Doctor of Philosophy in mathematics, statistics and operations research). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/568

Mellalieu, P. J., & Hall, K. R. (1983). An Interactive Planning Model for the New Zealand Dairy Industry. Journal of the Operational Research Society, 34, 521–532. doi:10.1057/jors.1983.119

Kearney, T. D., Hall, K. R., & Mellalieu, P. J. (1984). Recent Advances in Network Optimization Methods and Applications. Proceedings of the Annual Conference of the United Kingdom Operational Research Society. Presented at the Annual Conference of the United Kingdom Operational Research Society. Retrieved from http://unitec.academia.edu/PeterMellalieu/Papers/1569500/Recent_Advances_in_Network_Optimization_Methods_and_Applications

The trend of operations research/management science activity towards the construction of models that will be used... more The trend of operations research/management science activity towards the construction of models that will be used recurrently for decision making leads naturally towards the concept of Decision Support Systems (DSS). Factors influencing this trend are identified, and the movement towards DSS construction in New Zealand is reviewed through examination of several successful NZ applications.

To meet the demand for more formal approaches to strategic planning the idea of a Decision Support Group is introduced. A brief examination beyond DSS is made in which it is suggested that more automated methods for implementing management decisions will complete the ‘management control’ cycle.

Vibration and symmetry-breaking of boron-nitride nanotubes

by Rajib Chowdhury

Nanotechnology, 2010

The unique features of axial, torsional, transverse and radial breathing vibrations are captured for armchair and... more The unique features of axial, torsional, transverse and radial breathing vibrations are captured for armchair and zigzag singlewalled boron nitride nanotubes (BNNTs) based on molecular mechanics simulations and continuum mechanics theories. Equivalent Young's modulus 1TPa and shear modulus 0.4TPa are obtained independent of the chirality of BNNTs. In particular, a distorted optimized structure is observed for the first time for BNNTs with sufficiently large diameter and length. It is found that the deformed structures result in the behaviours of BNNTs deviating from those of classical columns/beams. Such symmetry breaking could also exert significant impacts on the structural instability (buckling) and the electronic properties of BNNTs that are sensitive to the structural symmetry.

Multidisciplinary Design Optimization of Long Endurance

by Ranjan Ganguli

Rajagopal, S., and Ganguli, R., “Multidisciplinary Design Optimization of Long Endurance Unmanned Aerial Vehicle Wing”, Computer Modeling in Engineering and Science, Vol. 81, No. 1, 2011, pp. 1-34.

Hydro Power Plants Operation Optimization using an On-offline Approach

by Guilherme Bastos

Draft only. Published in 54th POWID Annual ISA Symposium

This paper presents a proposal for the optimization of the operation of hydro power plants by the optimal distribution... more This paper presents a proposal for the optimization of the operation of hydro power plants by the optimal distribution of the dispatched power among its power generating units. Some optimization algorithms are presented and com-pared for the simulation and optimization of the Rio Bonito small hydro. Effi-ciency curves of the units were obtained from field tests.

Automated Optimization of Process Plant Using Particle Swarm Optimization

by Muhammad Shariq Khan

This paper appears in:
Advanced Control of Industrial Processes (ADCONIP), 2011 International Symposium on
Date of Conference: 23-26 May 2011
Author(s): Khan, M.S.
Sch. of Chem. Eng., Yeungnam Univ., Gyeongsan, South Korea
Husnil, Y.A. ;  Yong Soo Kwon ;  Moonyong Lee
On Page(s): 615 - 620
Product Type: Conference Publications

Nowadays general-purpose process plant simulators are used widely in industry and in academia, reason being process... more Nowadays general-purpose process plant simulators are used widely in industry and in academia, reason being process model can be developed more rigorously with fewer endeavors and the graphical user interface makes the realization of model less time consuming. During the development phase of a process model we often have a lot of variables that has to vary to get the best solution among several candidates. The automation potential of the simulator can be exploited to look for the best solution by varying these variables under some optimization scheme. In this study the Particle Swarm Optimization was used to optimize the process plant under the automation of process simulator Hysys. In the case study Natural Gas liquefaction plant was used to optimize and results show that the method can save energy and improves the process efficiency.

Thermoeconomic Analysis of Simple Trigeneration Systems

by Monica Carvalho

M. A. Lozano, M. Carvalho, J. C. Ramos, L. M. Serra

Trigeneration is the combined production of heating, cooling and power from the same source of energy. In this paper,... more Trigeneration is the combined production of heating, cooling and power from the same source of energy. In this paper,
the operation of a simple trigeneration system is analyzed. The system is interconnected to the electric utility grid, both
to receive electricity and to deliver surplus electricity. For any given demand required by the users, a great number of
operating conditions are possible. The operational mode with  the lowest variable cost is obtained through a linear
programming model. Three different approaches to determine the costs of internal flows and final products of the
simple trigeneration systems are presented: marginal costs corresponding to optimal operation, costs obtained when
production costs are distributed to the final products according to their market prices, and internal costs corresponding
to a thermoeconomic analysis of the operation mode of the system. As expected, the costs obtained with the approaches
mentioned are different and it can be concluded that there are no general rules to decide which approach is best: it
depends on the issue under investigation.

Optimal load distribution between units in a power plant

by Guilherme Bastos

Published on ISA Transactions 2007, pp. 533-539

This paper presents a strategy for load distribution between the generating units in hydro power plants. The objective... more This paper presents a strategy for load distribution between the generating units in hydro power plants. The objective is to reach the maximum energy conversion efficiency for a given dispatched power. The developed tool employs a heuristic-based combinatorial optimization technique in conjunction with a set of system variables measurement allowing real-time load sharing. The developed equipment is used to give online energy conversion efficiency from each unit of the power plant. No specific previous information about the efficiency of system components is required. Simulation results of the proposed optimization technique when applied to typical hydro power plant data are presented.

Evapotranspiration data assimilation with genetic algorithms and SWAP model for on-demand irrigation

by Baburao Kamble

From the first intention movement to the last joiner: macaques combine mimetic rules to optimize their collective decisions

by Cedric Sueur

An Efficient Hierarchical Parallel Genetic Algorithm for Graph Coloring Problem

by Malek Mouhoub

! NOMINATED FOR BEST PAPER AWARD AT GECCO 2011 !

R. Abbasian and M. Mouhoub. An efficient hierarchical parallel genetic algorithm for graph coloring problem, 13th Annual Genetic and Evolutionary Computation Conference (GECCO 2011), ACM, pages 521-528, Dublin, Ireland, July 12-16, 2011. Also presented at the International Joint Conferences on Artificial Intelligence (IJCAI 2011), RCRA, July 2011.

Graph coloring problems (GCPs) are constraint optimization problems with various applications including scheduling,... more Graph coloring problems (GCPs) are constraint optimization problems with various applications including scheduling, time tabling, and frequency allocation. The GCP consists in finding the minimum number of colors for coloring the graph vertices such that adjacent vertices have distinct colors. We propose a parallel approach based on Hierarchical Parallel Genetic Algorithms (HPGAs) to solve the GCP. We also propose a new extension to PGA, that is Genetic Modification (GM) operator designed for solving constraint optimization problems by taking advantage of the properties between variables and their relations. Our proposed GM for solving the GCP is based on a novel Variable Ordering Algorithm (VOA). In order to evaluate the performance of our new approach, we have conducted several experiments on GCP instances taken from the well known DIMACS website. The results show that the proposed approach has a high performance in time and quality of the solution returned in solving graph coloring instances taken from DIMACS website. The quality of the solution is measured here by comparing the returned solution with the optimal one.

Ant Colony with Stochastic Local Search for the Quadratic Assignment Problem

by Malek Mouhoub

M. Mouhoub and Z. Wang. Ant Colony with Stochastic Local Search for the Quadratic Assignment Problem. The 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'06). pages 143-149, Washington, November 13-15, 2006

The existing Ant Colony Optimization (ACO) Algorithms for the Quadratic Assignment Problem (QAP) are often combined... more The existing Ant Colony Optimization (ACO) Algorithms for the Quadratic Assignment Problem (QAP) are often combined with two kinds of Stochastic Local Search (SLS) methods: the 2-opt local search and the tabu local search. In this paper, these two SLS methods are respectively improved according to the properties of ACO and QAP. For the 2-opt local search, a new random walk strategy is used to avoid a quick stagnation into local optima. Moreover, a forward-looking strategy is proposed to explore the neighborhood more thoroughly. In the case of tabu local search, a random walk strategy is also employed to avoid getting stuck at local optima. Experimental evaluation of the ACO algorithms combined with the improved local search proposed in this paper are conducted on problems from the well known QAPLIB library. The results demonstrate that each ACO algorithm, combined with its respective improved local search, has a better performance, in terms of the quality of the solution returned, than the ACO algorithm with the original local search techniques. Moreover, we also noticed that the improved methods outperform each other for different classes of problems.

Secondary Coordination at Closely‐Spaced Actuated Traffic Signals

by Lee D. Han

ASCE Journal of Transportation Engineering (2011) 137(11):751-759
with Xiaoli Sun and Tom Urbanik

This paper presents a method of addressing stochastic variation at closely spaced signalized intersections to provide... more This paper presents a method of addressing stochastic variation at closely spaced signalized intersections to provide secondary coordination to “minor” movements with significant traffic volumes. A neuro fuzzy signal control system was designed in this study to manage a non-coordinated movement to avoid queue spillback. Building on the conventional actuated-coordinated control system, the neuro-fuzzy controller does not lose the benefit of the primary coordination of the conventional controller but establishes a “secondary coordination” between the upstream coordinated phase (through phase) and the downstream non-coordinated phase (left-turn phase) on the basis of areal-time traffic demand. Under the neuro-fuzzy signal control, the traffic from the upstream intersection can arrive and join the queue at the downstream left-turn lane and be served in a timely fashion and thus reduce the likelihood of being delayed at the downstream intersection. The simulation results indicate that the neuro-fuzzy signal control consistently outperformed the conventional actuated-coordinated controller in terms of reduction in systemwide average delay and number of stops per vehicle under a wide range of traffic volumes by nearly 20% under heavier demand conditions.

Painting by Numbers: Nanoparticle‐Based Colorants in the Post‐Empirical Age

by Robin Klupp Taylor

An empirical study of optimization for maximizing diffusion in networks

by Bistra Dilkina

A Proposed Four-Level Fuzzy Logic for Traffic Signal Control

by Lee D. Han

TRB 04-0510 (2004)
with Zhenyang LI and Hui WANG

Optimal signal phases control deals with a complex multi-objective and multi-constraint problem in which the... more Optimal signal phases control deals with a complex multi-objective and multi-constraint problem in which the optimization is based mainly on real-time information. All existing fuzzy logic control models are limited to predetermined phase orders with the abilities to skip and extend phases. However, they cannot add or rearrange phases to fulfill the greater potential of fuzzy control and, hence, better performance. To address this issue, this study proposed a four-level fuzzy logic traffic control model, which optimizes the operations at signalized intersections. The four levels of fuzzy logic control include traffic situation level, phase status level, phase order level, and green ending or extending level. To implement this control model, observed approaching traffic flows are used to estimate relative traffic intensities in the competing approaches. These traffic intensities are then used to determine whether a leading or lagging signal phase should be selected or terminated.

The performance of this four-level fuzzy logic traffic signal control model compared favorably in all categories to fixed time control, actuated control, and other traditional fuzzy control based on simulations using field data. The results suggest that the proposed four-level fuzzy logic signal control model to be a superior and efficient tool for reducing intersection traffic delay. The study also demonstrated that the successful implementation of the proposed model does not rely on the installation of expensive or complicated equipment.

Follow-up research effort is under way to use additional field data to continuously calibrate, validate, and improve membership functions and implementation process to further improve the performance of the model.

Short-Term Hydro Scheduling with Discrepant Objectives Using Multi-Step Progressive Optimality Algorithm

by K.W. Chau

Chuntian Cheng, Jianjian Shen, Xinyu Wu, and Kwok-wing Chau (2012). Journal of the American Water Resources Association, (JAWRA) 1-16. DOI: 10.1111 ⁄ j.1752-1688.2011.00628.x

With increase in the number and total capacity of hydropower plants in power systems, optimality algorithms with a... more With increase in the number and total capacity of hydropower plants in power systems, optimality algorithms with a single objective are not suitable for optimizing the operation of complex hydropower systems to meet complex demands. Hydropower plants should prioritize discrepant objectives, such as peak regulation and maximizing generation during solving of optimal operation problems of hydropower systems. In this article, we present a multi-step progressive optimality algorithm (MSPOA) for the short-term hydroscheduling (STHS) problem to improve the quality of optimal solutions and enhance the convergence speed of progressive optimality algorithm (POA). In MSPOA, the original problem is first decomposed into a sequence of problems with the longer time steps. Next, the problem with the longest time step is solved, and the optimal solution is used as the initial solution for the problem with the second longest time step. This process proceeds until the original problem with the shortest time step is solved. The proposed discrepant-objective method and solution technique are tested for two types of hydroelectric systems. The results show that MSPOA can give better solutions and cost less time than POA due to enlarging feasible range of decision variables and reducing the number of computational stages. Discrepant objectives among hydropower plants can express the operation characteristics of complex hydropower systems more accurately than unique objective or multiple objectives.