Portfolio models can serve as an assessment tool for the optimal assignment of capital between the potential investment projects in the various conditions for upstream companies. This process is ...crucial for any company if it wants to balance the short-term goals and seeks to maximize long-term value of the company. The paper aims to present a practical model of forming oil upstream company’s portfolio. The unique feature of this model is an individual approach to investment plan forming in a context of three types of projects: exploration, oil production and infrastructure projects. This is due to the individual approach which is used for comparison of all projects by using of universal set of indicators. Suggested model uses the multi-criteria selection mechanism by means of aggregating the key estimating indicators into the final project rank score. In that way the task of forming investment project’s portfolio of upstream company is a linear programming problem that is solved by simplex method. In the paper the model forms consolidated investment portfolio that takes into account decision makers’ preferences in setting of limits for resources.
Long‐term design and planning of shale gas field development is challenging due to the complex development operations and a wide range of candidate locations. In this work, we focus on the ...multi‐period shale gas field development problem, where the shale gas field has multiple formations and each well can be developed from one of several alternative pads. The decisions in this problem involve the design of the shale gas network and the planning of development operations. A mixed‐integer linear programming (MILP) model is proposed to address this problem. Since the proposed model is a large‐scale MILP, we propose a solution pool‐based bilevel decomposition algorithm to solve it. Results on realistic instances demonstrate the value of the proposed model and the effectiveness of the proposed algorithm.
Dynamic facility layout planning (DFLP) involves determining an appropriate arrangement scheme of the elements making up the production system for each time period into which the planning horizon is ...divided. When formulating the problem as an optimisation model, using the traditional top-down approach is usual, which firstly determines the block layout (BL) and then the detailed layout (DL) of each work cell. However by this approach, the BL generates area constraints in the detailed phase, which sometimes limit its implementation. In this context, the present paper presents a multi-objective mixed integer non-linear programming (MOMINLP) model that allows the problem to be addressed by considering an alternative approach, known in the literature as the bottom-up approach. The proposed model, called bottom-up mDFLP, considers three objective functions: (1) minimise the total material handling cost (TMHC) and the total rearrangement cost (TRAC); (2) maximise the total closeness rating (TCR) between departments; (3) maximise the area utilisation ratio (AUR). The original MOMINLP is transformed into a more computationally efficient multi-objective mixed integer linear programming (MOMILP) model. The proposed model is applied and validated in a case study of a company in the metal-mechanic sector with 12 departments for three 4-month periods.
In this paper, the decentralized energy management of a community of prosumers is studied. The coordination of the prosumers participating in the community is cast as a mixed-integer linear program ...(MILP) with local and global coupling constraints. A dual decomposition method with a tightening of the coupling constraints is applied to solve the problem in a decentralized way. The resulting tightened problem provides feasibility guarantees for the obtained solutions. A receding horizon approach that exploits the structure of the problem is proposed to divide the problem in subproblems and solve them sequentially. The proposed approach ensures that the tightened problem is feasible under realistic conditions, whereas the existing methods may result in infeasible problems. Moreover, it may reduce the necessary constraint tightening compared to existing methods. Two setups are evaluated for the organizational structure of the community, one with a community coordinator and one without. Moreover, three different structures of the communication graph are analyzed for the setup without a coordinator. The simulation results demonstrate that the proposed method results in feasible problems that can be solved due to the reduced constraint tightening when other methods are not feasible. In the case of feasible problems, the optimality gap is comparable to that achieved with existing methods and even smaller for communities with a small number of participating prosumers.
•This paper presents a mixed integer linear programming (MILP) model to optimize vehicle trajectories and traffic signals in a unified framework at isolated signalized intersections in a CAV ...environment.•Phase sequences, green start and duration of each phase, and cycle lengths are optimized together with vehicle lane-changing behaviors and vehicle arrival times for delay minimization.•Vehicle trajectories are determined by optimal control models and car-following models on the basis of optimized arrival times with the objective to minimize fuel consumption and emission.•Simulation results validate the advantages of the proposed control method over vehicle actuated control in terms of intersection capacity, vehicle delays, and CO2 emissions.
Existing traffic signal control systems only allocate green time to different phases to avoid conflicting vehicle movements. With advances in connected and automated vehicle (CAV) technologies, CAV trajectories not only provide more information than existing infrastructure-based detection systems, but also can be controlled to further improve mobility and sustainability. This paper presents a mixed integer linear programming (MILP) model to optimize vehicle trajectories and traffic signals in a unified framework at isolated signalized intersections in a CAV environment. A new planning horizon strategy is applied to conduct the optimization. All vehicle movements such as left-turning, right-turning and through are considered. Phase sequences, green start and duration of each phase, and cycle lengths are optimized together with vehicle lane-changing behaviors and vehicle arrival times for delay minimization. Vehicles are split into platoons and are guaranteed to pass through the intersection at desired speeds and avoid stops at stop bars. Exact vehicle trajectories are determined based on optimized vehicle arrival times. For the trajectory planning of platoon leading vehicles, an optimal control model is implemented to minimize fuel consumption/emission. For following vehicles in a platoon, Newell's car-following model is applied. Simulation results validate the advantages of the proposed control method over vehicle-actuated control in terms of intersection capacity, vehicle delays, and CO2 emissions. A sensitivity analysis is conducted to show the potential benefits of a short minimum green duration as well as the impacts of no-changing zones on the optimality of the proposed model.
Continuous-thrust relative reachable set is presented for the spacecraft linear relative motion near elliptical orbits. Two cases with different constraints are considered: the energy-constrained ...case and the fuel-constrained case. Based on the distance-fields-over-grids method, the envelopes of the relative reachable sets for both cases are approximated by a number of grid points on it, and these grid points are obtained from a series of optimization problems. Based on the continuous-thrust analytical state propagation, the original optimization problems for both cases are converted into the nonlinear programming problems. Furthermore, for the energy-constrained case, the analytical solution is obtained by using the Lagrange multiplier method; whereas for the fuel-constrained case, the problem is converted into a mixed-integer linear programming problem to rapidly obtain solutions. Several numerical examples are provided to verify that the developed methods for solving the spacecraft relative reachable sets are feasible and computationally efficient.
In this paper we analyze a continuous version of the maximal covering location problem, in which the facilities are required to be linked by means of a given graph structure (provided that two ...facilities are allowed to be linked if a given distance is not exceed). We propose a mathematical programming framework for the problem and different resolution strategies. First, we provide a Mixed Integer Non Linear Programming formulation for the problem and derive some geometrical properties that allow us to reformulate it as an equivalent pure integer linear programming problem. We propose two branch-&-cut approaches by relaxing some sets of constraints of the former formulation. We also develop a math-heuristic algorithm for the problem capable to solve instances of larger sizes. We report the results of an extensive battery of computational experiments comparing the performance of the different approaches.
•We introduce a framework for the Continuous MCLP with Interconnected Facilities.•We derive a Mixed Integer Second Order Cone Optimization formulation for the problem.•We provide a pure Integer Programming formulation for the problem.•We derive two branch and cut approaches for solving planar instances.•We develop a novel math-heuristic approach for the problem.
The integration of distributed generation units and microgrids in the current grid infrastructure requires an efficient and cost effective local energy system design. A mixed-integer linear ...programming model is presented to identify such optimal design. The electricity as well as the space heating and cooling demands of a small residential neighbourhood are satisfied through the consideration and combined use of distributed generation technologies, thermal units and energy storage with an optional interconnection with the central grid. Moreover, energy integration is allowed in the form of both optimised pipeline networks and microgrid operation. The objective is to minimise the total annualised cost of the system to meet its yearly energy demand. The model integrates the operational characteristics and constraints of the different technologies for several scenarios in a South Australian setting and is implemented in GAMS. The impact of energy integration is analysed, leading to the identification of key components for residential energy systems. Additionally, a multi-microgrid concept is introduced to allow for local clustering of households within neighbourhoods. The robustness of the model is shown through sensitivity analysis, up-scaling and an effort to address the variability of solar irradiation.
•Distributed energy system planning is employed on a small residential scale.•Full energy integration is employed based on microgrid operation and tri-generation.•An MILP for local clustering of households in multi-microgrids is developed.•Micro combined heat and power units are key components for residential microgrids.
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