Optimal Expansion Strategy Research Articles

Economically-efficient port expansion strategies: An optimal control approach

This paper proposes an analytical model with a control approach to obtain an optimal port expansion strategy by balancing investment costs for the port and congestion costs for its users. Starting point is the optimality condition that marginal investment costs should balance marginal benefits. Particularly the scale effect in investment costs is considered; the consequence that the investment will be made in different stages is included in the solution. By relaxing some assumptions in the model, a numerical optimization algorithm is proposed which is applied to show how the approach can be used to deal with a practical expansion problem.

Dynamic Capacity Expansion for a Service Firm with Capacity Deterioration and Supply Uncertainty

Motivated by the challenges faced by the telecom industry during the past decade, in this paper we study a dynamic capacity expansion problem for service firms. There is a random demand for the firm's capacity in each period: the demand in excess of the capacity is lost, and revenue is generated for the fulfilled demand. At the beginning of each period, the firm might increase its capacity through purchasing equipment for immediate delivery, which is constrained by a random supply limit, or it might sign a future contract for equipment delivery in the following period. We assume that the firm's capacity might partially become obsolete due to natural deterioration or technology innovation. We aim at characterizing optimal capacity expansion strategies and comparing the profit functions as well as the optimal control policies of different options. Specifically, we show that the optimal capacity expansion policy for the current period is determined by a base-stock policy. Compared with the case where no future contracts are available, the optimal control parameters of capacity expansion are always smaller. We further show that when the obsolescence rate is deterministic, the optimal policy for capacity expansion through future contracts is also a base-stock type. The results are extended to the cases with stochastically dependent capacity supply limits and stochastically dependent demand processes, which establish the robustness of the optimal policy in various market conditions.

Development of a Strategy for Port Expansion: An Optimal Control Approach

Development of economically efficient expansion strategies for ports and transport infrastructure in general is highly relevant in view of the increasing need for justification of public funding for such projects. Optimisation of the investment and congestion costs, taking into account economies of scale and utilisation rate, and addressing the questions of when, with what size and with what relief interval capacity a port should be expanded, constitutes a generic problem in the planning of infrastructure. The derivation of such strategy, using optimal control theory and incorporating the balance between marginal investment costs and marginal benefits (here, reduction of congestion costs), is presented in this paper. The outcome is applied to a typical port planning problem, in which the optimal expansion strategy is determined for a container port that is confronted with steady demand growth. Recommendations comprise directions for further extension of the proposed modelling approach by the (1) use of non-linear demand patterns, (2) introduction of competition and (3) consideration of internal efficiency improvement alternatives. Major investments in Dutch ports, such as a second seaward expansion of Rotterdam port – a €2.9 billion project – and the presence of fierce competition between European seaports illustrate the relevance of this research effort.

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.

Optimal expansion of a developing power system under the conditions of market economy and environmental constraints

This paper presents a mathematical model for the optimal expansion of a developing power system. The relations between technical and economic criteria of the power system are non-linear, which makes the problem more complicated. In this model all non-linear relations are made linear. The considered model includes provisions for energy security, which is significant especially for countries that do not possess adequate energy resources. Furthermore, environmental constraints are placed on the model to formulate optimal expansion strategy for the developing power system. Based on the economic analysis of the model some conclusions and recommendations are made.

A MODELLING APPROACH FOR INTEGRATED PLANNING OF PORT CAPACITY- TRADE-OFFS IN ROTTERDAM INVESTMENT PLANNING

This paper presents a modelling approach for planning ofport capacity. The approach integrates port commercial andpublic interests. It further incorporates route competition andautonomous demand growth. It is applied to port expansion,which can be considered as a strategy for an individual port todeal with route competition. The basis for solving this planningproblem comprises an analysis of port demand and supply in apartial equilibrium model. With such an approach, the reactionof a single port on the change in a transport network comprisingalternative routes to a hinterland destination can be simulated.To establish the optimal expansion strategy, port expansion iscombined with congestion pricing. This is used for the simultaneousdetermination of 1) optimal expansion size, and 2) investmentrecovery period. The modelling approach will be appliedto Rotterdam port focusing on port expansion by means ofland reclamation. The scenmio of the entry of a new competingroute via the Italian port Gioia Tauro is used to address sometrade-offs in Rotterdam investment planning.

Ant Colony Search Algorithm for Optimal Strategical Planning of Electrical Distribution Systems Expansion

Strategical planning is one of many research fields in the design of electrical distribution systems. The problem of strategical planning is a multiobjective combinatorial problem and the search space may often be quite large concerning to the options. The aim is to identify a strategy of expansion of a given distribution system in a given timeframe. For this problem, the search space is created beforehand by running a multiobjective optimisation algorithm for the optimal design of distribution networks for different load levels related to different years. The sets of Pareto-optimal solutions obtained for each load level at each year are equivalent in terms of the considered objectives, these being minimum losses, installation costs, and minimum unavailability. The problem of the identification of the optimal expansion strategy through these chronologically intermediate solutions leading to the final target configuration at the last year has been solved herein using an ACS (Ant Colony Search) algorithm. In order to verify the efficiency of the ACS algorithm, a small size application has been carried out and results have been compared to those obtained with enumeration. Then, a Simulated Annealing (SA) approach was used for a larger size test problem and results were compared to those obtained using the ACS. For this problem, the ACS demonstrated to be more robust than SA with higher quality results.

Optimal Expansion of Water Quality Monitoring Network by Fuzzy Optimization Approach

River reaches are frequently classified with respect to various mode of water utilization depending on the quantity and quality of water resources available at different location. Monitoring of water quality in a river system must collect both temporal and spatial information for comparison with respect to the preferred situation of a water body based on different scenarios. Designing a technically sound monitoring network, however, needs to identify a suite of significant planning objectives and consider a series of inherent limitations simultaneously. It would rely on applying an advanced systems analysis technique via an integrated simulation-optimization approach to meet the ultimate goal. This article presents an optimal expansion strategy of water quality monitoring stations for fulfilling a long-term monitoring mission under an uncertain environment. The planning objectives considered in this analysis are to increase the protection degree in the proximity of the river system with higher population density, to enhance the detection capability for lower compliance areas, to promote the detection sensitivity by better deployment and installation of monitoring stations, to reflect the levels of utilization potential of water body at different locations, and to monitor the essential water quality in the upper stream areas of all water intakes. The constraint set contains the limitations of budget, equity implication, and the detection sensitivity in the water environment. A fuzzy multi-objective evaluation framework that reflects the uncertainty embedded in decision making is designed for postulating and analyzing the underlying principles of optimal expansion strategy of monitoring network. The case study being organized in South Taiwan demonstrates a set of more robust and flexible expansion alternatives in terms of spatial priority. Such an approach uniquely indicates the preference order of each candidate site to be expanded step-wise whenever the budget limitation is sensitive in the government agencies.

Multi-objective, decision-based assessment of a water quality monitoring network in a river system.

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.

External costs: an attempt to make power generation a fair game (case study Croatia)

External costs of electricity represent the monetary value of the environmental damage caused by electricity generation. They are here calculated applying the impact pathway methodology on Croatian specific conditions. This paper estimates the external costs of coal and gas fired power plants determined as main candidates for Croatian power system expansion till 2030. It is analyzed how the estimated external costs, when incorporated into total production costs, would affect the competitiveness of fossil–fired plants compared to other electricity generation options, i.e. how they influence the optimal expansion strategy of the Croatian power system.

An expert system with fuzzy sets for optimal planning

This paper describes a long range power system expansion planning program which incorporates three significant features. It is an optimising program and uses dynamic programming for tracking an optimal expansion strategy. Secondly it contains a rule based decision making mechanism to incorporate engineering judgement based on design office experience and expert opinions, and finally, since some of these considerations have to be cast in qualitative terms and needs to balance many conflicting requirements, fuzzy set theory has been used to formulate a portion of the decision making procedure

An expert system with fuzzy sets for optimal planning (of power system expansion)

A description is given of a long-range power system expansion planning program which incorporates three significant features. First, it is an optimizing program and uses dynamic programming for tracking an optimal expansion strategy. Second, it contains a rule-based decision making mechanism to incorporate engineering judgment based on design office experience and expert opinions. Third, since some of these considerations have to be cast in qualitative terms and need to balance many conflicting requirements, fuzzy set theory has been used to formulate a portion of the decision making procedure.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Long range stochastic planning of generation considering overdesign

This paper presents a new model for the optimal expansion planning of generation facilities in Power Systems under uncertainties of demand forecasts and generator outages. The objective is to find an expansion strategy requiring minimum present worth of revenue requirements so that electric power can be supplied to consumers at a reasonably low price with high degree of reliability. System utility is evaluated in terms of its capacity to meet demand requirements under uncertain conditions. The design also aims at reducing the over design of the system which requires a large capital outlay. A method based on the preference order dynamic programming is presented to determine the long-range optimal expansion strategy. This avoids the drawbacks of the conventional dynamic programming methods and requires lesser number of alternatives to be considered for selection of the optimal expansion policy.