OR in strategic land-use planning

An important historic strategic application of OR has been in the field of land-use and development plan production. Changes in Government policy and legislation have led to varying levels of interest in plan production. Three post-war cycles of ‘enthusiasm for plans’ can be identified. Whilst the first was rooted very much in the Architectural Design tradition, the second led to significant developments in OR, with far wider application. Subsequent reduced Governmental enthusiasm for ‘Development Plan production’ led to considerable atrophy of relevant skills in the planning community, including those derived from OR. However, the current ‘third period of post-war enthusiasm for planning’, reinforced by environmental concerns, has revived the need for relevant skills. It is suggested that, whilst the deficit in skills and their application remains high, there are some encouraging signs. Moreover, substantial progress in the field of ‘soft OR’ offers opportunities to both the OR and planning communities.     

Criterion function for accessibility,uncertainty problems in regional land-use planning

One objective in regional planning is the creation of communities with great accessibility. Thus we should plan the locations of inhabitants and the activities of the region so that the total accessibility will be maximized subject to some restrictions. This is a quadratic programming problem, which can be solved by quadratic programming techniques, but we cannot then take into account the uncertainties of the problem.In this paper a new criterion function is proposed for accessibility, uncertainty problems in regional land-use planning. It is derived from Hurwicz's generalized maximin principle. Many advantages are gained, for the planning problem is separated into linear programming problems, the uncertainties are taken into consideration as in game theory and the methods of parametric programming are available.A simplified problem of the populations of three town areas is studied and the method is generalized for problems of many activities and areas.     

A multiobjective planning model for university resource allocation

Application of systematic approaches and dynamic planning for efficient resources allocation in institutions of higher education has been quite prevalent the past fifteen years. However, most models developed for university management have focused upon the analysis of input (budget/resource) requirements. They have generally neglected the existing environment, unique institutional values, and bureaucratic decision structures. In this study, a large scale goal programming model is developed for an efficient allocation of resources for an entire university for a five year planning period. The results of the model have been implemented in the form of administrative actions to achieve a set of multiple objectives.     

A genetic approach for strategic resource allocation planning

Enterprises often implement a measurement system to monitor their march towards their strategic goals. Although this way it is possible to assess the progress of each goal, there is no structured way to reconsider resource allocation to those goals and to plan an optimal (or near optimal) allocation scheme. In this study we propose a genetic approach to match each goal with an autonomous entity (agent) with a specific resource sharing behavior. The overall performance is evaluated through a set of functions and genetic algorithms are used to eventuate in approximate optimal behavior’s schemes. To outline the strategic goals of the enterprise we used the balanced scorecard method. Letting agents deploy their sharing behavior over simulation time, we measure the scorecard’s performance and detect distinguished behaviors, namely recommendations for resource allocation.     

Basin-wide cooperative water resources allocation

The Cooperative Water Allocation Model (CWAM) is designed within a general mathematical programming framework for modeling equitable and efficient water allocation among competing users at the basin level and applied to a large-scale water allocation problem in the South Saskatchewan River Basin located in southern Alberta, Canada. This comprehensive model consists of two main steps: initial water rights allocation and subsequent water and net benefits reallocation. Two mathematical programming approaches, called the priority-based maximal multiperiod network flow (PMMNF) method and the lexicographic minimax water shortage ratios (LMWSR) technique, are developed for use in the first step. Cooperative game theoretic approaches are utilized to investigate how the net benefits can be fairly reallocated to achieve optimal economic reallocation of water resources in the second step. The application of this methodology to the South Saskatchewan River Basin shows that CWAM can be utilized as a tool for promoting the understanding and cooperation of water users to achieve maximum welfare in a river basin and minimize the potential damage caused by water shortages, through water rights allocation, and water and net benefit transfers among water users under a regulated water market or administrative allocation mechanism.     

A structural framework for the design of integrated environmental and land-use planning optimization models

This study presents a structural framework for analyzing land-use/environmental interactions and formulating planning models accounting for these interactions. A general conceptual planning model is first developed. Its applicability is illustrated through a review of major environmental pollution transfer models, and through the development of a prototypical model that is progressively expanded to account for centralized treatments, transfer modifications, short-term and long-term dynamics, and the stochasticity of the environment.     

装载与运输路径的联合最优规划

运输问题中可以分为两个过程:分配装载和规划路径运输,后者是图论问题,前者因为涉及到分配不同的货物装载到不同的运输工具上,是非线性整数规划问题,所以整个问题也是NP复杂问题,随着问题复杂度的增加,变量增多,求解将会非常耗时和困难.提出了基于多旅行商的M-TSP图论装载运输优化模型,和对此模型进行简化后的基于确定路线的整数线性规划装载模型,从而极大的方便此类问题的快速求解,为实际生产运输商业行为提供了一种方便、科学、可靠的决策模型和方案.     

Fuzzy bicriteria multi-index transportation problems for coal allocation planning of Taipower

Taipower, the official electricity authority of Taiwan, encounters several difficulties in planning annual coal purchase and allocation schedule, e.g., with multiple sources, multiple destinations, multiple coal types, different shipping vessels, and even in uncertain demand and supply. In this study, these concerns are formulated as a fuzzy bicriteria multi-index transportation problem. Furthermore, an effective and interactive algorithm is proposed which combines reducing index method and interactive fuzzy multi-objective linear programming technique to cope with a complicated problem which may be prevalent in other industries. Results obtained in this study clearly demonstrate that this model can not only satisfy more of the actual requirements of the integral system but also offer more information to the decision makers (DMs) for reference in favor of exalting decision making quality.     

Combined time and energy optimal trajectory planning with quadratic drag for mixed discrete-continuous task planning

ABSTRACT

The problem of mixed discrete-continuous task planning for mechanical systems, such as aerial drones or other autonomous units, can be often treated as a sequence of point-to-point trajectories. In this work, the problem of optimal trajectory planning under a combined completion time and energy criterion, for a straight point to point path for a second-order system with quadratic under state (velocity) and control (acceleration) constraints is considered. The solution is obtained and proved to be optimal using the Pontryagin Maximum Principle. Simulation results for different cases are presented and compared with a customary numerical optimal control solver.     

Joint optimization of budget allocation and maintenance planning of multi-facility transportation infrastructure systems

Transportation infrastructure, such as pavements and bridges, is critical to a nation’s economy. However, a large number of transportation infrastructure is underperforming and structurally deficient and must be repaired or reconstructed. Maintenance of deteriorating transportation infrastructure often requires multiple types/levels of actions with complex effects. Maintenance management becomes more intriguing when considering facilities at the network level, which represents more challenges on modeling interdependencies among various facilities. This research considers an integrated budget allocation and preventive maintenance optimization problem for multi-facility deteriorating transportation infrastructure systems. We first develop a general integer programming formulation for this problem. In order to solve large-scale problems, we reformulate the problem and decompose it into multiple Markov decision process models. A priority-based two-stage method is developed to find optimal maintenance decisions. Computational studies are conducted to evaluate the performance of the proposed algorithms. Our results show that the proposed algorithms are efficient and effective in finding satisfactory maintenance decisions for multi-facility systems. We also investigate the properties of the optimal maintenance decisions and make several important observations, which provide helpful decision guidance for real-world problems.     

Berth allocation planning in the public berth system by genetic algorithms

This paper addresses the problem of determining a dynamic berth assignment to ships in the public berth system. While the public berth system may not be suitable for most container ports in major countries, it is desired for higher cost-effectiveness in Japan’s ports. The berth allocation to calling ships is a key factor for efficient public berthing. However, it is not calculated in polynomially-bounded time. To obtain a good solution with considerably small computational effort, we developed a heuristic procedure based on the genetic algorithm. We conducted a large amount of computational experiments which showed that the proposed algorithm is adaptable to real world applications.     

A weighted goal programming approach for replenishment planning and space allocation in a supermarket

We propose a mixed integer non-linear goal programming model for replenishment planning and space allocation in a supermarket in which some constraints on budget, space, holding times of perishable items, and number of replenishments are considered and weighted deviations from two conflicting objectives, namely profitability and customer service level, are minimized. We apply a minimum–maximum approach to introduce demand where the maximum demand is a function of price change and allocated space. Each item is presented in the form of multiple brands, probably exposed to price changes, competing to obtain more space. In addition to inventory investment costs, replenishment costs, and inventory holding costs we also include costs related to non-productive use of space. The order quantity, the amount of allocated showroom and backroom spaces, and the cycle time of joint replenishments are key decision variables. We also propose an extended model in which price is a decision variable. Finally we solve the model using LINGO software and provide computational results.     

Exergy-based water resource allocation of the mainstream Yellow River

Based on the water resource exergy including chemical exergy, thermal exergy, potential exergy and sediment exergy, the allocation of water resource exergy along the mainstream Yellow River is illuminated. The water resource exergy for different anthropocentric water uses is also classified as agricultural irrigation exergy, industrial exergy, urban domestic exergy and rural domestic exergy. Aquatic exergetic ecotope (AEE) index is proposed as an indicator of the river ecosystem status in view of resource characteristic of exergetic assessment. Finally, the influences of the intake water on the AEE indices are well illustrated to reveal the possible impacts of water allocation on the river ecosystem status.     

Simulation and optimization for crop water allocation based on crop water production functions and climate factor under uncertainty

In this paper, the uncertainty methods of interval and functional interval are introduced in the research of the uncertainty of crop water production function itself and optimal allocation of water resources in the irrigation area. The crop water production functions in the whole growth period under uncertainty and the optimal allocation of water resources model in the irrigation area under uncertainty are established, and the meteorological factor is considered in the model. It can promote the practical application of the uncertain methods, reflect the complexity and uncertainty of the actual situation, and provide more reliable scientific basis for using water resources economically, fully improving irrigation efficiency, and keeping the sustainable development of the irrigated area. This approach has important value on theoretical and practical for the optimal irrigation schedule, and has very broad prospects for research and development to other related agriculture water management.     

A multiobjective optimization model for water resources planning

A technique is developed for solving multiple objective optimization programs. The approach decomposes the system into groups of objectives according to their priority in the model. A lexicographic ordering (goal programming) approach is used to analyse this system of groups, while the solution structure of each individual group is developed using the method of constraints. The technique is applied to a planning model for river basins.     

A stochastic programming model for water resource planning

A framework is offered for the evaluation of electricity generation and water supply for agricultural irrigation. This assessment is conducted through the construction of an appropriate stochastic optimization model. A recursive least squares algorithm is incorporated in the model which enables more accurate estimation of model parameters.     

A decisional procedure for water resources planning taking into account water quality constraints

This paper describes an approach for water resources planning taking into account both quantity and quality aspects. A decisional procedure is proposed which consists of two phases. In the first phase, the water resources sharing problem is dealt with, taking into account the demands of the various water users and the requirement of a minimum flow in any section of the river. In the second phase, the problem of fulfilling water quality standards is considered. This may require to reformulate the water resources sharing problem in order to increase the water flow in the river.     

Flatness based trajectory planning for the shallow water equations

A flatness based feed-forward control design approach for an open channel flow modelled by the shallow water equations is discussed. The control input consists of the adjustable height of opening of a delimiting sluice gate. In order to compute the trajectory of the control input, the problem is reduced to an initial value problem w.r.t. the spatial coordinate. The solution to this problem can be obtained with the method of characteristics. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Inexact de Novo programming for water resources systems planning

This study presents an interval de Novo programming (IDNP) approach for the design of optimal water-resources-management systems under uncertainty. The model is derived by incorporating the existing interval programming and de Novo programming, allowing uncertainties represented as intervals within the optimization framework. The developed IDNP approach has the advantages in constructing optimal system design via an ideal system by introducing the flexibility toward the available resources in the system constraints. A simple numerical example is introduced to illustrate the IDNP approach. The IDNP is then applied to design an inexact optimal system with budget limit instead of finding the optimum in a given system with fixed resources in a water resources planning case. The results demonstrate that the developed method efficiently produces stable solutions under different objectives. Optimal supplies of good-quality water are obtained in considering different revenue targets of municipal–industrial–agricultural competition under a given budget.