Electricity generation is considered to be one of the main contributing sources to the air pollution problem. It is, therefore, important to develop and implement effective control strategies to prevent the expected a...
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Electricity generation is considered to be one of the main contributing sources to the air pollution problem. It is, therefore, important to develop and implement effective control strategies to prevent the expected abrupt increase in emissions from this sector. Any control strategy must be suitable for local implementation and must also be economically viable. The main objective of this paper is to present optimisation models that can be used to determine the most cost effective strategy or combination of strategies to reduce CO2 emissions to a specific level. Optimisation results for an existing network of power plants show that it may be possible to reduce CO2 emissions by increasing power plant efficiency through a variety of adjustments in the plants. These include fuel balancing, fuel switching, and the implementation of improvement technologies to existing power plants to increase their thermal efficiency.
In traditional scheduling problems, most literature assumes that the processing time of a job is fixed. However, there are many situations where the processing time of a job depends on the starting time or the positio...
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In traditional scheduling problems, most literature assumes that the processing time of a job is fixed. However, there are many situations where the processing time of a job depends on the starting time or the position of the job in a sequence. In such situations, the actual processing time of a job may be more or less than its normal processing time if it is scheduled later. This phenomenon is known as the "learning effect''. In this study, we introduce a time-dependent learning effect into a single-machine scheduling problem. The objective function of the problem is minimization of the maximum lateness. This study shows that EDD rule, which guarantees the best solution in classical situation (without learning effect), can not guarantee the best results in the situation with learning effect. In addition, a non-linear programming model is proposed for this problem, and solutions are found for problems which have up to 14 jobs.
This paper presents a new methodology to determine fleet size and structure for those airlines operating on hub-and-spoke networks. The methodology highlights the impact of stochastic traffic network flow effects on f...
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This paper presents a new methodology to determine fleet size and structure for those airlines operating on hub-and-spoke networks. The methodology highlights the impact of stochastic traffic network flow effects on fleet planning process and is employed to construct an enhanced revenue model by incorporating the expected revenue optimization model into fleet planning process. The objective of the model is to find a feasible allocation of aircraft fleet types to route legs using minimum fleet purchasing cost, thus ensuring that the expected fleet profit is maximized subject to several critical resource constraints. By using a linear approximation to the total network revenue function, the fleet planning model with enhanced revenue modeling is decomposed into the nonlinear aspects of expected revenue optimization and the linear aspects of determining fleet size and structure by optimal allocation of aircraft fleet types to route legs. To illustrate this methodology and its economic benefits, an example consisting of 6 chosen aircraft fleet types, 12 route legs, and 57 path-specific origin-destination markets is presented and compared with the results found using revenue prorated fleet planning formulation. The results show that the fleet size and structure of the methodology proposed in this paper gain 211.4% improvement in fleet profit over the use of the revenue prorated fleet planning approach. In addition, comparison with the deterministic model reveals that the fleet size and structure of this proposed methodology are more adaptable to the fluctuations of passenger demands. Copyright (c) 2016 John Wiley & Sons, Ltd.
Congestion charging is considered an effective way to solve traffic congestion. In this paper, the main idea of solving road traffic congestion is to pay for some roads that are prone to congestion, and to compensate ...
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Congestion charging is considered an effective way to solve traffic congestion. In this paper, the main idea of solving road traffic congestion is to pay for some roads that are prone to congestion, and to compensate for other underutilized roads, this paper proposes a new method based on delay function to compensate for the secondary gradient road traffic compensation. Firstly, a nonlinearprogrammingmodel of toll/subsidy for road set is given, which is based on Beckmann minimization objective function, and then the conditional constraint of model is established by using Kuhn-Sears and Lagrange multipliers. Secondly, based on heuristic algorithm, the pricing compensation strategy of road traffic is established, the delay function analysis model is established by using marginal cost, then the model is optimized based on the secondary gradient method, finally, the validity of the algorithm is validated by the simulation experiment on the real road network. (C) 2018 Elsevier Ltd. All rights reserved.
Aircraft conflict resolution is of great importance for the safe and efficient management of air traffic. This study proposes a two-step optimization approach for the aircraft conflict resolution problems within the p...
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Aircraft conflict resolution is of great importance for the safe and efficient management of air traffic. This study proposes a two-step optimization approach for the aircraft conflict resolution problems within the pre-tactical time window in generic free route airspace. Safe separation between aircraft pairs is maintained using either altitude or heading angle change maneuvers in a pre-defined buffer zone within the boundaries of the airspace. The first step of the model aims to minimize the total number of conflicting aircraft and the total fuel consumption together using altitude change maneuvers. A mixed-integer linearprogrammingmodel is proposed for the first step but, due to the high computational time, a metaheuristic algorithm (simulated annealing) was developed. If the altitude change does not resolve all conflicts in the first step, the proposed model implements heading angle change maneuvers with minimum extra fuel burn in the second step. A nonlinearprogrammingmodel is presented for the second step. Numerical results show that the proposed approach can resolve all conflicts in less than 4 min for the highest traffic flow rate.
In this paper, flowshop scheduling problem with a learning effect is considered. The objective function of the problem is minimizing completion times variance. A non-linear programming model is developed for the probl...
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In this paper, flowshop scheduling problem with a learning effect is considered. The objective function of the problem is minimizing completion times variance. A non-linear programming model is developed for the problem. Also the model is tested on an example. Results of computational tests show that the proposed model is effective in solving problems with up to 30 jobs. The overall average solution error of the heuristic algorithm is 2 %. Processing of the 30 jobs case requires only 0.1 s on average to obtain an ultimate or even optimal solution. To solve the large sizes problems up to 500 jobs, heuristics methods were used. The performances of heuristics about the solution error were evaluated with the non-linear programming model results for small size problems and each other for large size problems. According to results, the special heuristic for all number of jobs was the more effective than others. The heuristic scheduling algorithm is more practical to solve real world applications than the non-linear programming model.
While making profit plan, the multinational corporations often reduce the profits of enterprises with heavy taxation burden according to taxation burden of subsidiaries, and transfer the reduced profits to the enterpr...
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ISBN:
(纸本)9781424481194
While making profit plan, the multinational corporations often reduce the profits of enterprises with heavy taxation burden according to taxation burden of subsidiaries, and transfer the reduced profits to the enterprises in which the taxation burden is light. This simple complementary approach to profit planning is not only constrained by the restriction of the volume of business between subsidiaries and the cost of transferring profits, but also more importantly is constrained by restricting factors such as tax authority's anti-avoiding taxation so that the resulting effect of profit planning is not excellent. On the basis of analyzing spatial profit planning, multinational corporations make a decision considering the objectives and restrictions of tax minimization, establishing a non-linear programming model, solving the optimal limit of profit-shifting and determining the optimal tax planning program. Taking Lenovo Group for example, inspects the validity of the model.
In terms of the design of the Core Section, aiming at the half of the core circumcircle, for the case of the Core Section without the Cooling Oil Pan, this paper firstly establishes a non-linear programming model taki...
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ISBN:
(纸本)0878492712
In terms of the design of the Core Section, aiming at the half of the core circumcircle, for the case of the Core Section without the Cooling Oil Pan, this paper firstly establishes a non-linear programming model taking the objective function that the geometric cross-sectional area of the column core is the largest. Then, on the basis of analyzing the case of Cross Section with the Cooling Oil Pans another non-linear programming model is estabished to make the geometric cross-sectional area of the core column be the largest and the adjacent area of the two parts divided by the Cooling Oil Pans be equal as much as possible. And, the series of the section and the width and thickness of the silicon steel sheets at all levels are fixed while the effective cross-section of the core column is maximum. At last, to the two instances, this paper analyses the effects of the addition of the Cooling Oil Pans on the design for Cross Section.
When large scale emergency incident happens, the multi-category emergency goods distribution is a complex problem. To improve structure and efficiency of emergency goods distribution, a multi-objective non-linear opti...
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ISBN:
(纸本)9781424473281
When large scale emergency incident happens, the multi-category emergency goods distribution is a complex problem. To improve structure and efficiency of emergency goods distribution, a multi-objective non-linear optimization programmingmodel for emergency goods distribution is established. modeling precondition is analyzed in detail, some objectives such as minimizing the waiting time, the transportation cost, the preference of selecting emergency commodity distribution center (ECDC) and so on are taken into account. The constraints of the model including total demand quantity and structure of disaster area, the transportation quantity and time from each ECDC are considered. The penalty factor method is employed to transform above model into an easy one, then GA is employed. The encoding system for multi-category emergency goods distribution is introduced, and the basic implement steps of GA are given in detail. The typical instance abstracted from practice is adopted to validate the validity of above model and algorithm, the experiment result shows that above model can describe the practical demand of multi-category emergency goods distribution, and GA is suitable for solving some complex non-linearprogramming problems such as multi-category emergency goods distribution. Above model and algorithm will benefit for the emergency goods distribution practice.
This study proposes a dynamic trip pricing (DTP) problem considering the distribution imbalances of cars in one-way station-based carsharing systems. In the DTP problem, the trip prices are functions of the balancing ...
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ISBN:
(纸本)9781728158556
This study proposes a dynamic trip pricing (DTP) problem considering the distribution imbalances of cars in one-way station-based carsharing systems. In the DTP problem, the trip prices are functions of the balancing degrees of both origin and destination stations. The DTP problem aims to maximize the expected profit of the carsharing system in a given planning horizon. A non-linear programming model is built for the DTP problem and solved by a particle swarm optimization algorithm. The proposed methods are validated and evaluated based on a larger number of randomly generated instances. The results indicate that the DTP scheme results in profit increment and car distribution improvement, which helps enhance user satisfactions. The sensitivity analysis shows that the scheme is also helpful when the user price elasticities are varied. Furthermore, the DTP scheme is applicable to different types of price-demand relationship.
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