Linear Programming Optimization Model Research Articles

Cost-effective species conservation: an application to Huemul (Hippocamelus bisulcus) in Chile

In this paper we study the cost-effective allocation of the land in the Cordilleran Protection Area (CPA), Region VIII, Chile, for the conservation of a highly threatened species: the Huemul (Hippocamelus bisulcus). Using a production possibilities frontier (PPF) approach, a linear programming optimization model for a ten-year time period is proposed. Our model takes into account both the preferences of the species for different habitats and the opportunity cost of the land. We evaluate different possibilities of land allocation and identify cost-effective alternatives in the provision of both conservation and income.The results confirm the hypothesis that both the population of Huemul and income from economic activities can be increased compared with current levels. Therefore the current allocation of the land in the CPA is not cost-effective.

Watershed-based self- and peer-appraisal indices for integrated environmental assessment with a case study of the Mid-Atlantic region

Environmental indicators are often aggregated into a single index in environmental studies. Commonly, an aggregated index is derived in a specific weighting scheme imposed from the outside. The paper presents a novel approach by letting each unit under study choose a set of weights. It applies the concept of self- and cross-appraisal in generating various aggregated indices from two linear programming optimization models. The proposed method is illustrated via a case study of the Mid-Atlantic region. Results show that the derived aggregated indices reveal environmental conditions of the study area in an objective and robust fashion. The proposed method is a valuable tool for integrated environmental assessment.

Fuzzy Multiobjective and Linear Programming Based Management Models for Optimal Land-Water-Crop System Planning

In this article, linear programming and fuzzy optimization models are developed for planning and management of available land-water-crop system of Mahanadi-Kathajodi delta in eastern India. The models are used to optimize the economic return, production and labour utilization, and to search the related cropping patterns and intensities with specified land, water, fertilizer and labour availability, and water use pattern constraints. Due to extreme backwardness of the study area, it has been decided to keep all the three objectives of the linear programming models at the same priority level to obtain the compromised solution in a fuzzy environment that incorporates the imprecision in fuzzy goals and fuzzy constraints. These non-structural models facilitate the conjunctive use of available surface water and groundwater resources. A comparative evaluation along with the benefit-cost ratios of the existing and proposed farming systems is also presented.

Mathematical modeling analyses for obtaining an optimal railway track maintenance schedule

Railway track irregularities need to be kept at a satisfactory level by taking appropriate maintenance activities. This paper aims at obtaining an optimal maintenance schedule for improving the railway track irregularities using all-integer linear programming (AILP) optimization model analyses. Firstly, we try to predict a change of surface irregularities by investigating the transition process through degradation and restoration model analyses. Then we develop an AILP model for obtaining an optimal schedule of multiple tie tamper (MTT) operation. The model takes both maintenance costs and the level of surface irregularities that reflects riding quality and safety into account, then finally gives an optimal tamping schedule of MTT for the whole year. Then we apply the results of this model to solve the optimal MTT’s maintenance scheduling problem for the actual railway network system and show that it is effective and useful enough by comparing our model results with actual existing data.

Integrated chain analysis of recycled vis-a-vis wood pulp paper industry: an Indian manufacturer viewpoint

Strict environmental regulations and the ever-increasing shortages in the availability of natural resources are making reverse logistics an area of growing importance. From the manufacturer's point of view, this paper proposes a linear programming optimisation model for the Indian paper industry with two different sources of raw materials (i.e., wood and wastepaper). The objective of the model is to minimise the paper supply chain cost, which includes costs of collection, transportation, segregation and disposal (for recycled paper), inventory, and manufacturing. The inclusions of environmental cost and cost of quality added a new dimension to the said model, which was not explored earlier in the supply chain context. To know the behaviour of the system under different scenarios, sensitivity analysis, shortage analysis and finally, indifference curve analysis have been performed on the model. The model will help the manufacturer make strategic decision under different shortage scenarios of the paper supply chain.

A Decomposition Method for the Simultaneous Planning and Scheduling of Single-Stage Continuous Multiproduct Plants

In this paper, we address the problem of simultaneously integrating the planning and scheduling of continuous multiproduct plants that consist of a single processing unit. We present a multiperiod mixed-integer linear programming (MILP) optimization model that is based on a continuous time representation, which becomes computationally very expensive to solve as the length of the planning horizon increases. To circumvent this problem, a rigorous bilevel decomposition algorithm is proposed to reduce the computational cost of the problem. The original simultaneous model is decomposed into an upper level planning problem and a lower level planning and scheduling problem. The upper level determines the potential products to be processed, their production levels, and inventories. The lower level is solved in the reduced space of binary variables and determines production levels, product inventories, and the detailed sequence of products and their corresponding processing times. Integer cuts and logic cuts are proposed to reduce the feasible search space for the binary variables and to tighten the gap between the solutions of the two levels. Numerical examples for problems ranging from 4 to 24 weeks are presented to illustrate the performance of the algorithm and to compare it with a full space solution.

Performance-Net: A Decision Support System for Reconfiguring a Bank's Branch Network

This paper presents a Decision Support System (DSS) that enables the management of a retail bank to evaluate and reconfigure its branch network. The DSS uses computational methods and knowledge that arises from information about the bank's operational and fixed costs, as well as demographic characteristics from the geographical area where branches are located. The DSS that we call Performance-Net estimates the performance of a branch network and determines the optimum number of branches and the optimum mix of services that each one should provide in order to maximize the bank's revenue- generating measures. Its computational engine is based on a linear programming optimization model and its implementation is developed using the standard MS Excel program. Performance-Net provides efficient solutions, is particularly user-friendly and can reach excellent answers for a wide variety of “what if” parametric scenarios.

Wastewater reuse potential analysis: implications for China's water resources management

It has been recognized that wastewater reuse or reclamation serves as an efficient and valuable way to cope with the scarcity of water resources and severity of water pollution. This paper presents the systematic framework of wastewater reuse potential estimation. Based on the regional disparities in China, a linear programming optimization model is developed to explore the potential wastewater reuse quantities, under physical and economic constraints. Sensitivity analysis and Robust Counterpart (RC) optimization are performed to discuss the influences of key parameters and the reuse quantity's decision making under uncertainty. Based on the model, effectiveness of different policy scenarios of water price changes are simulated and evaluated, providing information regarding China's water and wastewater management.

CO 2 mitigating effects by waste heat utilization from industry sector to metropolitan areas

A huge amount of waste heat is emitted annually to the environment by energy intensive industries. Thermally activated advanced absorption cycles can be promising candidates for utilizing the waste heat of industry sector. In such absorption systems, it is desirable to utilize the waste heat from industries for heating and cooling applications in commercial and residential sectors. For this purpose, it is necessary to transport energy over some distance because the waste heat source and demand are generally located apart from each other. Transportation of steam, hot water or chilled water requires high construction costs for insulation. There is an efficient method of energy transportation using absorption system called “solution transportation absorption (STA) system”. The solution is transported at an ambient temperature so that tube-insulation is not required. This paper shows system analysis of the above-mentioned system and the optimal result, using mathematical optimization. The mathematical model is a demand driven linear programming (LP) optimization model which provides useful energy demand for a metropolitan area by industry waste heat supply and transportation of energy through STA system. The optimum energy system with and without introducing STA system in the long-term energy planning is obtained. At the end, the effect on the pollution emission and fossil fuel based energy conservation is obtained.

CO2 mitigating effects by waste heat utilization from industry sector to metropolitan areas

A huge amount of waste heat is emitted annually to the environment by energy intensive industries. Thermally activated advanced absorption cycles can be promising candidates for utilizing the waste heat of industry sector. In such absorption systems, it is desirable to utilize the waste heat from industries for heating and cooling applications in commercial and residential sectors. For this purpose, it is necessary to transport energy over some distance because the waste heat source and demand are generally located apart from each other. Transportation of steam, hot water or chilled water requires high construction costs for insulation. There is an efficient method of energy transportation using absorption system called “solution transportation absorption (STA) system”. The solution is transported at an ambient temperature so that tube-insulation is not required. This paper shows system analysis of the above-mentioned system and the optimal result, using mathematical optimization. The mathematical model is a demand driven linear programming (LP) optimization model which provides useful energy demand for a metropolitan area by industry waste heat supply and transportation of energy through STA system. The optimum energy system with and without introducing STA system in the long-term energy planning is obtained. At the end, the effect on the pollution emission and fossil fuel based energy conservation is obtained.

A Reliability-Based Approach to Transmission Maintenance Planning and Its Application in BC Hydro System

This paper presents a reliability-based method for transmission maintenance planning. A quantified impact assessment of the planned outage on operation reliability of the whole transmission system is a main feature of the proposed method. This reliability centered maintenance (RCM) approach for transmission systems provides not only the lowest risk maintenance schedule but also the most reliable operation mode for the planned outage. Another feature of the method is ease of incorporation into the existing traditional transmission maintenance procedure. A time-shift-based Monte Carlo simulation technique and a linear programming optimization model are used to perform reliability evaluation of the transmission system with planned outage(s). An example for the planned replacement of a 230-kV cable in the BC Hydro North Metro system has been given to demonstrate a practical application of the proposed procedure and the method.

Scheduling of a multiproduct pipeline system

Pipelines provide an economic fluid transportation mode for petroleum systems, especially when large amounts of petroleum derivatives have to be pumped for long distances. The system reported in this paper is composed by an oil refinery, one multiproduct pipeline connected to several depots and to the local consumer markets that receive large amounts of oil products. Extensive distances must be covered to reach the depots and the pipeline operates intermittently due to periodic increases in energy costs. The pipeline is divided into segments that connect two consecutive depots and packs that contain one product that compose the segments. Mixed-integer linear programming optimization models that are generated from linear disjunctions and rely on discrete time are proposed for the scheduling system. In the first model it is assumed that the pipeline is divided into packs of equal size, whereas the second one relaxes such assumption. Key decisions of this model involve loading and unloading operations of tanks and of the pipeline These models satisfy all operational constraints, such as mass balances, distribution constraints, product demands, sequencing constraints and logical constraints for pipeline operation. Results generated include the inventory levels at all locations, the distribution of products among the depots and the best ordering of products in the pipeline. Two examples are solved, including a real-world system that is composed of five depots and distributes gasoline, diesel, liquefied petroleum gas and jet fuel for a 3-day time horizon.

Simulation and Control of Chlorine Levels in Water Distribution Networks

Chlorine concentration is an important parameter used to assess the quality of water supplied by a distribution network. While several water quality simulators are readily available (e.g., EPANET software), water quality optimization decision support tools are currently lacking. A new control-oriented calculation model for chlorine concentrations in distribution networks is presented for general water distribution networks operating under periodic demand conditions. The model is based upon the analysis of the characteristic curves of the concentration transport-reaction equation over each pipe in a network. Numerical results are comparable with EPANET results, but unlike other water quality algorithms, the current method requires neither discretizations along the pipes, nor the choice of initial conditions. Moreover, it is a first step toward a method for controlling concentrations, yielding linear relationships between the concentrations at both ends of each pipe by the explicit inclusion of system dynamics. These relationships can be used as constraints in a linear programming optimization model that minimizes deviations from permissible concentration levels.

Optimization of land use structure based on ecological GREEN equivalent

Optimization of land use structure consists of economic and social and ecological optimization. Applying the minds of system engineering and principles of ecology, this paper presents such thoughts: the optimal forest-coverage rate calculated according to the reality of a district is set as main standard of ecological rationality in the district; through considering the value of ecosystem services of the land with GREEN equivalent (mainly cultivated land and grassland) and based on the rule, GREEN equivalent, this paper introduces the area conversion between woodland and cultivated land, also between woodland and grassland; this paper establishes a multi-dimension controlling model of optimization of land use structure. In addition, a multi-objective linear programming model for optimization of land use structure is designed. In the end, this paper tests and verifies this theory of ecological optimization, taking Qionghai city in Hainan Province as an example.

Optimal Crop Planning and Conjunctive Use of Water Resources in a Coastal River Basin

Due to increasing trend of intensive rice cultivation in a coastal river basin, crop planning and groundwater management are imperative for the sustainable agriculture. For effective management, two models have been developed viz. groundwater balance model and optimum cropping and groundwater management model to determine optimum cropping pattern and groundwater allocation from private and government tubewells according to different soil types (saline and non-saline), type of agriculture (rainfed and irrigated) and seasons (monsoon and winter). A groundwater balance model has been developed considering mass balance approach. The components of the groundwater balance considered are recharge from rainfall, irrigated rice and non-rice fields, base flow from rivers and seepage flow from surface drains. In the second phase, a linear programming optimization model is developed for optimal cropping and groundwater management for maximizing the economic returns. The models developed were applied to a portion of coastal river basin in Orissa State, India and optimal cropping pattern for various scenarios of river flow and groundwater availability was obtained.

An inter-seasonal agricultural water allocation system (SAWAS)

This paper introduces a linear programming optimization model for analyzing inter-seasonal allocation of irrigation water in quantities and qualities and their impact on agricultural production and income. The SAWAS model is a developed version of the Agricultural Sub-Model (AGSM). In this research, we stress water scarcity as a problem that arises when water is not found in proper quantity and quality at the appropriate place and time. The model is designed to serve as a decision-making tool for planners of agricultural production on both the district and the regional level. It generates an optimal mix of water-demanding activities that maximizes the net agricultural income of the districts and gives the water demands under various prices. It also provides the planner with tools to carry out ‘what-if’ experiments and to generate optimal water demand curves. A principal feature of SAWAS is the use of demand and the benefits from water together with costs and optimization within the agricultural sector to specify the optimal usage of different water qualities. Hence the agricultural planner can use the outputs of SAWAS in order to bridge the gap between the limited water resources and the increased agricultural production in an area that suffers from severe water scarcity. The paper applies the SAWAS model to the Jordan Valley in Jordan.

Modeling uncertainty of induced technological change

Modeling uncertainty of induced technological change

Pinch locations at heat capacity flow-rate disturbances of streams for minimum utility cost heat exchanger networks

The work deals with heat exchanger network (HEN) targeting under heat capacity flow-rates of streams disturbances. In particular, the aim is to calculate all pinches that can exist in a HEN with utilities of minimum cost when stream heat capacity flow-rates ( CPs) are allowed to change within given ranges. It is assumed that the disturbances are stochastic. The knowledge of pinches at certain as well uncertain data is of great importance in designing HENs. For instance, Pinch Technology is based on pinch phenomenon and its influence on HEN operation and design. In case of parameter disturbances, this is even more important since additional application in HEN’s control (see e.g. [1,2]). It is worthnoting that in case of disturbances, pinches behave in very complex manner as it was shown in [1–5]. A rigorous approach has been developed for calculating all feasible locations of pinches that can occur in minimum utility cost of HENs operating at varying heat capacity flow-rates of process streams. The method is based on recursive solution of mixed-integer linear programming (MILP) optimisation model that requires quite moderate number of binary variables. Examples of method application and analysis of results are presented in the work.

Optimization of the Regional Municipality of Ottawa-Carleton's water supply system operations. I. Model development

The principal objective of this study was to optimize pump scheduling and reservoir releases in the Regional Municipality of Ottawa-Carleton's (RMOC) water supply system with a view to reducing electricity-related operating costs. Pump schedules and reservoir releases for enhanced operation were obtained using a linear programming optimization model that incorporated Ottawa Hydro's electricity tariff structure for "large" users. A second objective was to investigate the impact on system operating costs of increasing (i) reservoir storage capacity, (ii) treatment plant capacity, and (iii) water demand by consumers. This paper (part I) describes the RMOC distribution system and reviews the model development. The next paper (part II) presents the analyses performed for the two study objectives, and important results. Key words: water supply system, pump scheduling, pumping costs, optimization, modelling.

A scheduling decision aid in glass fiber manufacturing

A decision aid for scheduling production in glass fiber manufacturing industry is described. The methodology combines a linear programming (LP) optimization model with a heuristic model. The LP model determines production goals; the heuristic model then uses the LP output to incorporate system-specific constraints in developing processing sequences.