Routing vehicles to minimize fuel consumption

We consider a generalization of the capacitated vehicle routing problem known as the cumulative vehicle routing problem in the literature. Cumulative VRPs are known to be a simple model for fuel consumption in VRPs. We examine four variants of the problem, and give constant factor approximation algorithms. Our results are based on a well-known heuristic of partitioning the traveling salesman tours and the use of the averaging argument.     

Hybrid heuristics for a short sea inventory routing problem

We consider a short sea fuel oil distribution problem where an oil company is responsible for the routing and scheduling of ships between ports such that the demand for various fuel oil products is satisfied during the planning horizon. The inventory management has to be considered at the demand side only, and the consumption rates are given and assumed to be constant within the planning horizon. The objective is to determine distribution policies that minimize the routing and operating costs, while the inventory levels are maintained within their limits. We propose an arc-load flow formulation for the problem which is tightened with valid inequalities. In order to obtain good feasible solutions for planning horizons of several months, we compare different hybridization strategies. Computational results are reported for real small-size instances.     

Optimality properties of speed optimization for a vessel operating with time window constraint

We consider speed optimization for a vessel that has to arrive at every port along its voyage within a time window at each port. The objective of the problem is to minimize the vessel’s bunker fuel cost given that fuel consumption rate is a convex function of speed. The intent of this paper is to establish the optimality properties for this problem and show that a solution with such properties (which we refer to as a good solution) is unique and optimal. The optimality properties established in this paper facilitate the proof of exactness for existing and future algorithms, as one needs only to show that the solution provided by an algorithm satisfies the definition of a good solution. As an illustration, we show how we can apply our results to prove the exactness of an existing algorithm in literature. Our work contributes to the understanding of the problem’s optimality structure, which will provide intuition for development of algorithms for this problem.     

A stochastic approach for the optimization of open-loop engine control systems

The operation of sensors and actuators in engine control systems is always affected by errors, which are stochastic in nature. In this paper it is shown that, because of the non-linear interactions between engine performance and control laws in an open-loop engine control system, these errors can give rise to unexpected deviations of control variables, fuel consumption and emissions from the optimal values, which are not predictable in an elementary way.A model for vehicle performance evaluation on a driving cycle is presented, which provides the expected values of fuel consumption and emissions in the case of stochastic errors in sensors and actuators, utilizing only steady-state engine data.The stochastic model is utilized to obtain the optimal control laws; the resultant non-linear constrained minimization problem is solved by an Augmented Lagrangian approach, using a Quasi-Newton technique. The results of the stochastic optimization analysis indicate that significant reductions in performance degradation may be achieved with respect to the solutions provided by the classical deterministic approach.     

航空器供油问题中完全逆序类中的多项式时间可解类

航空器供油问题是一类非线性组合优化问题,其目标函数为分式形式,该问题目前不存在多项式时间算法,也未被证明是NP完全问题。一般可以用置换来刻画n架飞机的一个供油顺序。该问题中有一类实例被称为“完全逆序类”,“完全逆序类”用动态规划算法求解计算时间为O(n2ⁿ),具有指数时间复杂度。本文通过对该“完全逆序类”问题做进一步分析,发现在“完全逆序类”中也存在着多项式时间可解的情况。定理1研究一类一次可解的情况,若问题满足定理1的条件,则求解一次即可找到其最优解;定理2研究一类多项式时间可解的情况,当问题满足定理2的条件时,其最优解可在多项式时间内获得。     

Reducing fuel emissions by optimizing speed on shipping routes

Fuel consumption and emissions on a shipping route are typically a cubic function of speed. Given a shipping route consisting of a sequence of ports with a time window for the start of service, substantial savings can be achieved by optimizing the speed of each leg. This problem is cast as a non-linear continuous program, which can be solved by a non-linear programming solver. We propose an alternative solution methodology, in which the arrival times are discretized and the problem is solved as a shortest path problem on a directed acyclic graph. Extensive computational results confirm the superiority of the shortest path approach and the potential for fuel savings on shipping routes.     

A Reduction Technique for Natural Gas Transmission Network Optimization Problems

We address the problem of minimizing the fuel consumption incurred by compressor stations in steady-state natural gas transmission networks. In the practical world, these type of instances are very large, in terms of the number of decision variables and the number of constraints, and very complex due to the presence of non-linearity and non-convexity in both the set of feasible solutions and the objective function. In this paper we present a study of the properties of gas pipeline networks, and exploit them to develop a technique that can be used to reduce significantly problem dimension, without disrupting problem structure, making it more amenable to solution.     

The Optimal Control of a Train

We consider the problem of determining an optimal driving strategy in a train control problem with a generalised equation of motion. We assume that the journey must be completed within a given time and seek a strategy that minimises fuel consumption. On the one hand we consider the case where continuous control can be used and on the other hand we consider the case where only discrete control is available. We pay particular attention to a unified development of the two cases. For the continuous control problem we use the Pontryagin principle to find necessary conditions on an optimal strategy and show that these conditions yield key equations that determine the optimal switching points. In the discrete control problem, which is the typical situation with diesel-electric locomotives, we show that for each fixed control sequence the cost of fuel can be minimised by finding the optimal switching times. The corresponding strategies are called strategies of optimal type and in this case we use the Kuhn–Tucker equations to find key equations that determine the optimal switching times. We note that the strategies of optimal type can be used to approximate as closely as we please the optimal strategy obtained using continuous control and we present two new derivations of the key equations. We illustrate our general remarks by reference to a typical train control problem.     

时变路网条件下联合配送的开放式车辆路径问题

针对城市物流系统中的多物流中心联合配送问题,设计一种多物流中心处理方法共享物流资源;分析城市路网的时变特性,设计路段行驶时间计算方法;综合考虑客户需求、时间窗、车辆不同出发时间、油耗、碳排放与联合配送模式等因素,以总成本最小为目标构建联合配送的开放式时变车辆路径规划模型,设计改进蚁群算法求解;实验结果表明以上方法具有可行性与有效性。     

Nonlinear optimal feedback control for lunar module soft landing

In this paper, the task of achieving the soft landing of a lunar module such that the fuel consumption and the flight time are minimized is formulated as an optimal control problem. The motion of the lunar module is described in a three dimensional coordinate system. We obtain the form of the optimal closed loop control law, where a feedback gain matrix is involved. It is then shown that this feedback gain matrix satisfies a Riccati-like matrix differential equation. The optimal control problem is first solved as an open loop optimal control problem by using a time scaling transform and the control parameterization method. Then, by virtue of the relationship between the optimal open loop control and the optimal closed loop control along the optimal trajectory, we present a practical method to calculate an approximate optimal feedback gain matrix, without having to solve an optimal control problem involving the complex Riccati-like matrix differential equation coupled with the original system dynamics. Simulation results show that the proposed approach is highly effective.     

A simulated annealing algorithm for transient optimization in gas networks

In this paper we present a simulated annealing approach for the gas network optimization problem. A gas network consists of a set of pipes to transport the gas from the sources to the sinks whereby gas pressure gets lost due to friction. Further on there are compressors, which increase gas pressure, and valves. The aim is to minimize fuel gas consumption of the compressors whereas demands of consumers have to be satisfied. The problem of transient (time-dependent) optimization of gas networks results in a highly complex mixed integer nonlinear program. We relax the equations describing the gas dynamic in pipes by adding these constraints combined with appropriate penalty factors to the objective function. A suitable neighborhood structure is developed for the relaxed problem where time steps as well as pressure and flow of the gas are decoupled. Our approach convinces with flexibility and very good computational results.     

The effect of diffusion on the autoignition of combustible fluids in insulation materials

The autoignition of flammable fluids in lagging materials isa major problem faced by the process industry. It is importantto ascertain whether such a system is safe or if it will undergoignition for a particular set of conditions. In this paper,a three-component model of this system is considered which includesexothermic oxidation and endothermic evaporation processes.By assuming a slow rate of consumption of fuel and oxygen, thebehaviour of the full system can be approximated and the safeand dangerous regions of parameter space can be identified.The effect of changes in parameters such as the size and theendothermicity are discussed in detail.     

Optimization out-of-orbit plane changes using aeroassisted maneuvers

The problem of optimizing the fuel consumption needed for orbital maneuvers is investigated. The normal to the orbit components of the atmospheric drag and lift forces are obtained. The temporal variations in the inclination using Lagrange planetary equation are derived, then are integrated over one revolution. A numerical example is given. The velocity variations required to perform the propulsive maneuvers due to engines on board the satellite are calculated. The performance gain using aerodynamic forces combined with propulsive ones is achieved. The comparison between the totally propulsive maneuvers and partly propulsive with atmospheric maneuvers are illustrated and discussed.     

Routing a mix of conventional,plug-in hybrid,and electric vehicles

We introduce an electric vehicle routing problem combining conventional, plug-in hybrid, and electric vehicles. Electric vehicles are constrained in their service range by their battery capacity, and may require time-consuming recharging operations at some specific locations. Plug-in hybrid vehicles have two engines, an internal combustion engine and an electric engine using a built-in rechargeable battery. These vehicles can avoid visits to recharging stations by switching to fossil fuel. However, this flexibility comes at the price of a generally higher consumption rate and utility cost.To solve this complex problem variant, we design a sophisticated metaheuristic which combines a genetic algorithm with local and large neighborhood search. All route evaluations, within the approach, are based on a layered optimization algorithm which combines labeling techniques and greedy evaluation policies to insert recharging stations visits in a fixed trip and select the fuel types. The metaheuristic is finally hybridized with an integer programming solver, over a set partitioning formulation, so as to recombine high-quality routes from the search history into better solutions. Extensive experimental analyses are conducted, highlighting the good performance of the algorithm and the contribution of each of its main components. Finally, we investigate the impact of fuel and energy cost on fleet composition decisions. Our experiments show that a careful use of a mixed fleet can significantly reduce operational costs in a large variety of price scenarios, in comparison with the use of a fleet composed of a single vehicle class.     

Environmentally conscious optimization of supply chain networks

The optimization of supply chain structures considering both economic and environmental performances is nowadays an important research topic. However, enterprises are commonly faced with the competing issues of reduced cost, improved customer service and increased environmental factors as a multi-faceted trade-off problem when designing supply chains. Hence, this paper proposes an environmentally conscious optimization model of a supply chain network with a broader and more comprehensive objective function that considers not just the transportation costs, but also the costs for the amount of greenhouse gas emissions, fuel consumption, transportation times, noise and road roughness. The paper sheds light on the trade-offs between various parameters such as vehicle speed, fuel, time, emissions, noise and their total cost, and offers managerial insights on economies of environmentally conscious supply chain optimization. An integer non-linear programming model is developed to help decision makers find the optimal solution under mentioned considerations. The proposed model is validated through the solution of an example, where its applicability to supply chain problems is demonstrated for managerial insights.     

Charge depleting range dynamic strategy with power feedback considering fuel-cell degradation

A charge depleting range dynamic strategy considering the fuel-cell degradation is proposed for the plug-in fuel cell hybrid electric vehicles in this paper, to seek the excellent economy performance with various driving ranges. The proposed strategy is developed by means of incorporating an adaptive equivalent factor into equivalent consumption minimization strategy with power feedback control. Firstly, the mathematical modeling of the proposed strategy is formulated to adjust the equivalent factor corresponding to the battery state of charge, which may vary with the forthcoming trip distance to dominate the expected energy consumption. The fuel cell voltage decay rate is applied to the feedback control of the restricted fuel-cell power, which is designed as the degradation model of fuel cell and integrated with the strategy. Secondly, the realization process of the charge depleting range dynamic strategy with restricted power feedback control model is a new attempt to design the real-time control method. Finally, the proposed strategy is validated by a numerical model developed by using the MATLAB/Simulink software and its effectiveness was evaluated by comparing it with the equivalent consumption minimization strategy. A sensitivity analysis is also conducted to study the effects of different trip distances. The effectiveness of power feedback control in fuel cell durability is validated through a hardware-in-the-loop experiment. The verified results demonstrate the influence of the equivalent factor on the control process, which makes the proposed strategy possible to provide significant improvement in the economy performance and fuel-cell durability.     

A weight-function approach for determining watershed initial conditions for combustion waves

In many generic combustion models, one finds that a combustionwave will develop with a specific wave speed. However, thereare possible initial temperature profiles which do not evolveinto such waves, but rather die out to the ambient temperature.There can exist, in some models, a clear distinction betweenthose initial conditions that do evolve into combustion wavesand those that do not; this is sometimes referred to as thewatershed initial condition. When fuel consumption is consideredto be negligible, analytical methods can be used to obtain theexact watershed. In this paper, we consider the problem of determiningpseudo-watersheds and ascertaining the relationship betweenthese pseudo-watersheds and the exact watersheds. In the processa novel weight-function approach for infinite spatial domainsis developed.     

Resource level minimization in the discrete–continuous scheduling

A discrete–continuous problem of non-preemptive task scheduling on identical parallel processors is considered. Tasks are described by means of a dynamic model, in which the speed of the task performance depends on the amount of a single continuously divisible renewable resource allotted to this task over time. An upper bound on the completion time of all the tasks is given. The criterion is to minimize the maximum resource consumption at each time instant, i.e., the resource level. This problem has been observed in many industrial applications, where a continuously divisible resource such as gas, fuel, electric, hydraulic or pneumatic power, etc., has to be distributed among the processing units over time, and it affects their productivity. The problem consists of two interrelated subproblems: task sequencing on processors (discrete subproblem) and resource allocation among the tasks (continuous subproblem). An optimal resource allocation algorithm for a given sequence of tasks is presented and computationally tested. Furthermore, approximation algorithms are proposed, and their theoretical and experimental worst-case performances are analyzed. Computer experiments confirmed the efficiency of all the algorithms.     

Maximum neutron flux in thermal research reactors

This paper deals with the determination of the space distribution of fuel concentration in thermal reactors for the purpose of obtaining maximum neutron flux. With some approximations, this problem is reduced to a nonclassical variational problem, which is solved by using Pontryagin's maximum principle. It is shown that the optimal fuel configuration of the reactor core consists of a reflector in its center, a zone of constant (permissible) power density, a zone of constant (maximum) fuel concentration, and a peripheral reflector of infinite thickness.     

A multiple period capacitated inventory model for airline fuel management: a case study

One of the major operating cost items of an airline company is fuel, which can amount to approximately 20% of its overall operating cost. This paper presents a decision support model that determines the amount of fuel to be uplifted by a plane at each station along its route over a predetermined planning horizon so as to minimise overall fuel costs. The aforementioned fuel management problem is modelled as a multiple period capacitated inventory problem and solved using linear programming. An example application illustrates the applicability of this model to Middle East Airline's (MEA) operations and summarises the dollar savings obtained by applying it over a one week planning horizon.