Home About us Contact
|
Home About us Contact | ||
|
|
||
Planning Problem (planning + problem)
Selected AbstractsOptimal Thermal Unit Commitment Integrated with Renewable Energy Sources Using Advanced Particle Swarm OptimizationIEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Issue 5 2009Shantanu Chakraborty Student member Abstract This paper presents a methodology for solving generation planning problem for thermal units integrated with wind and solar energy systems. The renewable energy sources are included in this model due to their low electricity cost and positive effect on environment. The generation planning problem also known by unit commitment problem is solved by a genetic algorithm operated improved binary particle swarm optimization (PSO) algorithm. Unlike trivial PSO, this algorithm runs the refinement process through the solutions within multiple populations. Some genetic algorithm operators such as crossover, elitism, and mutation are stochastically applied within the higher potential solutions to generate new solutions for next population. The PSO includes a new variable for updating velocity in accordance with population best along with conventional particle best and global best. The algorithm performs effectively in various sized thermal power system with equivalent solar and wind energy system and is able to produce high quality (minimized production cost) solutions. The solution model is also beneficial for reconstructed deregulated power system. The simulation results show the effectiveness of this algorithm by comparing the outcome with several established methods. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [source] Application and comparison of metaheuristic techniques to reactive power planning problemIEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Issue 6 2008Mehdi Eghbal Non-Member Abstract This paper presents the application and comparison of metaheuristic techniques to reactive power planning (RPP) problem which involves optimal allocation and combination of to-be-installed VAr sources to satisfy voltage constraints during normal and contingency states for multiple load levels. The main objective of the proposed RPP problem is to minimize the investment cost through balanced installation of SCs and SVCs while keeping a specified security level and minimizing the amount of load shedding. The problem is formulated as a large scale mixed integer nonlinear programming problem, which is a nonsmooth and nondifferentiable optimization problem using conventional optimization techniques and induces lots of local minima. Among the metaheuristic techniques, genetic algorithm (GA), particle swarm optimization (PSO) and evolutionary particle swarm optimization (EPSO) are applied to solve the RPP problem. To investigate the effectiveness of the metaheuristic techniques, the proposed approaches have been successfully tested on IEEE-14 buses, as well as IEEE-57 buses test system. The results obtained are compared and the effectiveness of each technique has been illustrated. Copyright © 2008 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [source] A multi-agent-based hybrid framework for international marketing planning under uncertaintyINTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 3 2009Shuliang Li The increased complexity and competition in the global marketing environment present new challenges to decision-makers. The characteristics of the international marketing planning problem are clarified in this paper. The advantages and disadvantages of relevant techniques and technologies that may be applied to deal with the planning problem are analysed. A multi-agent-based hybrid intelligent framework for international marketing planning and associated Internet strategy formulation is then established, with underlying techniques, technologies, software architecture and integration method outlined. In addition, a software prototype of the hybrid framework, called AgentsInternational, is created and presented, with initial evaluation results reported. Further work on this topic is also planned. Copyright © 2009 John Wiley & Sons, Ltd. [source] Integer programming solution approach for inventory-production,distribution problems with direct shipmentsINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 3 2008Miguel A. Lejeune Abstract We construct an integrated multi-period inventory,production,distribution replenishment plan for three-stage supply chains. The supply chain maintains close relationships with a small group of suppliers, and the nature of the products (bulk, chemical, etc.) makes it more economical to rely upon a direct shipment, full-truck load distribution policy between supply chain nodes. In this paper, we formulate the problem as an integer linear program that proves challenging to solve due to the general integer variables associated with the distribution requirements. We propose new families of valid cover inequalities, and we derive a practical closed-form expression for generating them, upon the determination of a single parameter. We study their performances through benchmarking several branch-and-bound and branch-and-cut approaches. Computational testing is performed using a large-scale planning problem faced by a North American company. [source] Coverage path planning algorithms for agricultural field machinesJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 8 2009Timo Oksanen In this article, a coverage path planning problem is discussed in the case of agricultural fields and agricultural machines. Methods and algorithms to solve this problem are developed. These algorithms are applicable to both robots and human-driven machines. The necessary condition is to cover the whole field, and the goal is to find as efficient a route as possible. As yet, there is no universal algorithm or method capable of solving the problem in all cases. Two new approaches to solve the coverage path planning problem in the case of agricultural fields and agricultural machines are presented for consideration. Both of them are greedy algorithms. In the first algorithm the view is from on top of the field, and the goal is to split a single field plot into subfields that are simple to drive or operate. This algorithm utilizes a trapezoidal decomposition algorithm, and a search is developed of the best driving direction and selection of subfields. This article also presents other practical aspects that are taken into account, such as underdrainage and laying headlands. The second algorithm is also an incremental algorithm, but the path is planned on the basis of the machine's current state and the search is on the next swath instead of the next subfield. There are advantages and disadvantages with both algorithms, neither of them solving the problem of coverage path planning problem optimally. Nevertheless, the developed algorithms are remarkable steps toward finding a way to solve the coverage path planning problem with nonomnidirectional vehicles and taking into consideration agricultural aspects. © 2009 Wiley Periodicals, Inc. [source] Flexible design-planning of supply chain networksAICHE JOURNAL, Issue 7 2009José Miguel Laínez Abstract Nowadays market competition is essentially associated to supply chain (SC) improvement. Therefore, the locus of value creation has shifted to the chain network. The strategic decision of determining the optimal SC network structure plays a vital role in the later optimization of SC operations. This work focuses on the design and retrofit of SCs. Traditional approaches available in literature addressing this problem usually utilize as departing point a rigid predefined network structure which may restrict the opportunities of adding business value. Instead, a novel flexible formulation approach which translates a recipe representation to the SC environment is proposed to solve the challenging design-planning problem of SC networks. The resulting mixed integer linear programming model is aimed to achieve the best NPV as key performance metric. The potential of the presented approach is highlighted through illustrative examples of increasing complexity, where results of traditional rigid approaches and those offered by the flexible framework are compared. The implications of exploiting this potential flexibility to improve the SC performance are highlighted and are the subject of our further research work. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] An attainable region approach for production planning of multiproduct processesAICHE JOURNAL, Issue 5 2007Charles Sung Abstract A novel approach is presented for the solution of production planning problems for multiproduct processes. A mixed-integer programming (MIP) scheduling model is analyzed off-line to obtain a convex approximation of feasible production levels and a convex underestimation of total production cost as a function of production levels. The two approximating functions are expressed via linear inequalities that involve only planning variables yet provide all the relevant scheduling information necessary to solve the planning problem with high quality. A rolling horizon algorithm is also presented for generation (if necessary) of detailed schedules. © 2007 American Institute of Chemical Engineers AIChE J, 2007 [source] A nested benders decomposition approach for telecommunication network planningNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 6 2010Joe Naoum-Sawaya Abstract Despite its ability to result in more effective network plans, the telecommunication network planning problem with signal-to-interference ratio constraints gained less attention than the power-based one because of its complexity. In this article, we provide an exact solution method for this class of problems that combines combinatorial Benders decomposition, classical Benders decomposition, and valid cuts in a nested way. Combinatorial Benders decomposition is first applied, leading to a binary master problem and a mixed integer subproblem. The subproblem is then decomposed using classical Benders decomposition. The algorithm is enhanced using valid cuts that are generated at the classical Benders subproblem and are added to the combinatorial Benders master problem. The valid cuts proved efficient in reducing the number of times the combinatorial Benders master problem is solved and in reducing the overall computational time. More than 120 instances of the W-CDMA network planning problem ranging from 20 demand points and 10 base stations to 140 demand points and 30 base stations are solved to optimality. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010 [source] A concave-cost production planning problem with remanufacturing optionsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 5 2005Jian Yang Abstract We focus on the concave-cost version of a production planning problem where a manufacturer can meet demand by either producing new items or by remanufacturing used items. Unprocessed used items are disposed. We show the NP-hardness of the problem even when all the costs are stationary. Utilizing the special structure of the extreme-point optimal solutions for the minimum concave-cost problem with a network flow type feasible region, we develop a polynomial-time heuristic for the problem. Our computational study indicates that the heuristic is a very efficient way to solve the problem as far as solution speed and quality are concerned. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005 [source] Wind power and ,the planning problem': the experience of WalesENVIRONMENTAL POLICY AND GOVERNANCE, Issue 5 2007Richard Cowell Abstract Across Europe, spatial planning has acquired an important role in steering wind power to more socially acceptable locations. However, the tendency for planning decisions to become a focus of opposition has also led to planning being represented as ,a problem' in meeting renewable energy targets. Using Jessop's dialectical relationship between modes and objects of governance, this paper seeks to understand why certain states are inclined to resolve ,the planning problem' for wind through strengthened national control. The case study is the Welsh Assembly Government's 2005 planning guidance on renewable energy, which superimposes centrally-determined ,Strategic Search Areas' for large-scale, onshore wind farm development onto local decision-making processes. Motivations for adopting this approach reflect the UK's centralizing planning culture, and beliefs that local planning processes will not yield sufficient sites to meet targets for wind power expansion. Responses to this planning guidance suggest that it may stabilizing the regulatory conditions for large-scale wind investment in the short term, in some parts of Wales, but faces a number of points of vulnerability in the longer term. Copyright © 2007 John Wiley & Sons, Ltd and ERP Environment. [source] Waste management modeling with PC-based model , EASEWASTEENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY, Issue 1 2008Gurbakhash S. Bhander Abstract As life-cycle-thinking becomes more integrated into waste management, quantitative tools are needed for assessing waste management systems and technologies. This article presents a decision support model to deal with integrated solid waste management planning problems at a regional or national level. The model is called EASEWASTE (environmental assessment of solid waste systems and technologies). The model consists of a number of modules (submodels), each describing a process in a real waste management system, and these modules may combine to represent a complete waste management system in a scenario. EASEWASTE generates data on emissions (inventory), which are translated and aggregated into different environmental impact categories, e.g. the global warming, acidification, and toxicity. To facilitate a "first level" screening evaluation, default values for process parameters have been provided, wherever possible. The EASEWASTE model for life-cycle-assessment of waste management is described and applied to a case study for illustrative purposes. The case study involving hypothetical but realistic data demonstrates the functionality, usability, and flexibilities of the model. The design and implementation of the software successfully address the substantial challenges in integrating process modeling, life-cycle inventory (LCI), and impact assessment (LCIA) modeling, and optimization into an interactive decision support platform. © 2008 American Institute of Chemical Engineers Environ Prog, 2008 [source] Power allocation in the context of dimensioning the air-interface of third generation W-CDMA-based cellular systemsINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 5 2002P. Demestichas Abstract The adoption of W-CDMA as an essential component of the air-interface of third-generation cellular systems brings to the foreground the need for new planning methodologies and software tools. In this perspective, this paper addresses planning problems that are important to the dimensioning of W-CDMA-based cellular networks. The problems aim at finding the optimal feasible allocation of transmission power to the sets of uplink and downlink connections that should be supported by the system, so as to cope with a corresponding traffic load scenario. The problems are concisely defined, mathematically formulated and solved by means of two computationally efficient, novel algorithms. The solutions of the problems may be seen as operating points at which the system performance should be driven. Finally, numerical results are presented and concluding remarks are drawn. Copyright © 2002 John Wiley & Sons, Ltd. [source] Constructing robust crew schedules with bicriteria optimizationJOURNAL OF MULTI CRITERIA DECISION ANALYSIS, Issue 3 2002Matthias Ehrgott Abstract Optimization-based computer systems are used by many airlines to solve crew planning problems by constructing minimal cost tours of duty. However, today airlines do not only require cost effective solutions, but are also very interested in robust solutions. A more robust solution is understood to be one where disruptions in the schedule (due to delays) are less likely to be propagated into the future, causing delays of subsequent flights. Current scheduling systems based solely on cost do not automatically provide robust solutions. These considerations lead to a multiobjective framework, as the maximization of robustness will be in conflict with the minimization of cost. For example crew changing aircraft within a duty period is discouraged if inadequate ground time is provided. We develop a bicriteria optimization framework to generate Pareto optimal schedules for the domestic airline. A Pareto optimal schedule is one which does not allow an improvement in cost and robustness at the same time. We developed a method to solve the bicriteria problem, implemented it and tested it with actual airline data. Our results show that considerable gain in robustness can be achieved with a small increase in cost. The additional cost is mainly due to an increase in overnights, which allows for a reduction of the number of aircraft changes. Copyright © 2003 John Wiley & Sons, Ltd. [source] An attainable region approach for production planning of multiproduct processesAICHE JOURNAL, Issue 5 2007Charles Sung Abstract A novel approach is presented for the solution of production planning problems for multiproduct processes. A mixed-integer programming (MIP) scheduling model is analyzed off-line to obtain a convex approximation of feasible production levels and a convex underestimation of total production cost as a function of production levels. The two approximating functions are expressed via linear inequalities that involve only planning variables yet provide all the relevant scheduling information necessary to solve the planning problem with high quality. A rolling horizon algorithm is also presented for generation (if necessary) of detailed schedules. © 2007 American Institute of Chemical Engineers AIChE J, 2007 [source] Approximation algorithms for general one-warehouse multi-retailer systemsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 7 2009Zuo-Jun Max Shen Abstract Logistical planning problems are complicated in practice because planners have to deal with the challenges of demand planning and supply replenishment, while taking into account the issues of (i) inventory perishability and storage charges, (ii) management of backlog and/or lost sales, and (iii) cost saving opportunities due to economies of scale in order replenishment and transportation. It is therefore not surprising that many logistical planning problems are computationally difficult, and finding a good solution to these problems necessitates the development of many ad hoc algorithmic procedures to address various features of the planning problems. In this article, we identify simple conditions and structural properties associated with these logistical planning problems in which the warehouse is managed as a cross-docking facility. Despite the nonlinear cost structures in the problems, we show that a solution that is within ,-optimality can be obtained by solving a related piece-wise linear concave cost multi-commodity network flow problem. An immediate consequence of this result is that certain classes of logistical planning problems can be approximated by a factor of (1 + ,) in polynomial time. This significantly improves upon the results found in literature for these classes of problems. We also show that the piece-wise linear concave cost network flow problem can be approximated to within a logarithmic factor via a large scale linear programming relaxation. We use polymatroidal constraints to capture the piece-wise concavity feature of the cost functions. This gives rise to a unified and generic LP-based approach for a large class of complicated logistical planning problems. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009 [source] A continuous-time strategic capacity planning model,NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 4 2005Woonghee Tim Huh Abstract Capacity planning decisions affect a significant portion of future revenue. In the semiconductor industry, they need to be made in the presence of both highly volatile demand and long capacity installation lead-times. In contrast to traditional discrete-time models, we present a continuous-time stochastic programming model for multiple resource types and product families. We show how this approach can solve capacity planning problems of reasonable size and complexity with provable efficiency. This is achieved by an application of the divide-and-conquer algorithm, convexity, submodularity, and the open-pit mining problem. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005. [source] Approximability of unsplittable shortest path routing problems,NETWORKS: AN INTERNATIONAL JOURNAL, Issue 1 2009Andreas Bley Abstract In this article, we discuss the relation of unsplittable shortest path routing (USPR) to other routing schemes and study the approximability of three USPR network planning problems. Given a digraph D = (V,A) and a set K of directed commodities, an USPR is a set of flow paths P, (s,t) , K, such that there exists a metric , = (,a) , Z with respect to which each P is the unique shortest (s,t)-path. In the Min-Con-USPR problem, we seek an USPR that minimizes the maximum congestion over all arcs. We show that this problem is NP-hard to approximate within a factor of O(|V|1,,), but polynomially approximable within min(|A|,|K|) in general and within O(1) if the underlying graph is an undirected cycle or a bidirected ring. We also construct examples where the minimum congestion that can be obtained by USPR is a factor of ,(|V|2) larger than that achievable by unsplittable flow routing or by shortest multipath routing, and a factor of ,(|V|) larger than that achievable by unsplittable source-invariant routing. In the CAP -USPR problem, we seek a minimum cost installation of integer arc capacities that admit an USPR of the given commodities. We prove that this problem is NP-hard to approximate within 2 , , even in the undirected case, and we devise approximation algorithms for various special cases. The fixed charge network design problem FC-USPR, where the task is to find a minimum cost subgraph of D whose fixed arc capacities admit an USPR of the commodities, is shown to be NPO-complete. All three problems are of great practical interest in the planning of telecommunication networks that are based on shortest path routing protocols. Our results indicate that they are harder than the corresponding unsplittable flow or shortest multi-path routing problems. © 2009 Wiley Periodicals, Inc. NETWORKS, 2009 [source] | ||||||||||||||||