Although optimization techniques have been successfully applied for a number of airline operations, aircraft recovery remains a challenge for both practitioners and researchers due to its complexity and the usual need...
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Although optimization techniques have been successfully applied for a number of airline operations, aircraft recovery remains a challenge for both practitioners and researchers due to its complexity and the usual need of a quick response in practical settings. In this paper, we consider the case of a Brazilian oil and gas company that uses a heterogeneous fleet of helicopters for passenger transportation from a few mainland aerodromes to maritime units. The major difficulties in rescheduling delayed flights are resource limitations and realistic features of the company combined with safety and management practices. The problem consists of determining joint daily flight reschedules for all aerodromes that satisfy operational constraints and recovers all pending flights, while minimizing flight transfers among aerodromes, usage of helicopters and overall flight delays. We propose a mixed integer programming (MIP) model, aiming to appropriately represent the problem, and MIP-based local search and two-phase heuristics to cope with larger realistic problem instances. Computational results obtained with instances collected in the case study show the potential of these approaches to deal with this real-life aircraft recovery problem.
In recent times, there has been a consistent need for companies to produce 'green' products and offer 'green' services in order to contribute to environmental protection. The utilisation of used device...
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In recent times, there has been a consistent need for companies to produce 'green' products and offer 'green' services in order to contribute to environmental protection. The utilisation of used devices (extending their useful life cycle) is an excellent, indirect way for companies to conform to this requirement and, at the same time, increase their profit. Cell phones constitute one of the most interesting cases of products, which can be returned, remanufactured and reused: their replacement rate is large, the available quantity for reuse is huge and, consequently, the profit potential is significant. Motivated by the real case of a company involved in the acquisition and remanufacturing of used cell phones, a simple mathematical programming model is proposed in this work that can help remanufacturing companies to make optimal decisions concerning the quantities to be purchased and remanufactured. Its use, namely the simulation of the model stochastic parameters and the optimisation of the model, reveals not only that the exploitation of used products can be profitable, but also that as the 'product acquisition system' improves, the economic benefits for any remanufacturing company can be even greater.
mixed integer programming formulations are presented for simultaneous or sequential balancing and scheduling of a flexible assembly line. The line is made up of a set of assembly stations in series, each with limited ...
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mixed integer programming formulations are presented for simultaneous or sequential balancing and scheduling of a flexible assembly line. The line is made up of a set of assembly stations in series, each with limited working space and is capable of simultaneously producing a mix of product types. The objective is to determine an assignment of assembly tasks to stations and an assembly schedule for all products so as to complete the products in a minimum time. Balancing and scheduling decisions can be made simultaneously or sequentially. In the latter approach first the station workloads are balanced, and then detailed assembly schedule is determined for prefixed task assignments and assembly routes by solving a standard job-shop problem. Balancing and scheduling with alternative or with single task assignments are considered. Numerical examples are provided and some computational results are reported to compare the two approaches.
This paper considers a collision avoidance problem of the vehicle and the moving obstacle. The prohibited region is defined for the vehicle and the obstacle considering a specified size of them. The problem is formula...
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This paper considers a collision avoidance problem of the vehicle and the moving obstacle. The prohibited region is defined for the vehicle and the obstacle considering a specified size of them. The problem is formulated as a mixed integer programming problem. In the problem the obstacles and environments around the automobile can be represent as inequality conditions. Then the driver assistance algorithm for the collision avoidance using the feasibility of the optimization is proposed. Computer simulation shows that the proposed algorithm can provide appropriate control input for collision avoidance.
This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective...
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This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise.
We consider the stochastic economic lot sizing problem with remanufacturing under customer service level constraints. The problem is a stochastic extension of the classical lot sizing problem where demand can be met v...
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We consider the stochastic economic lot sizing problem with remanufacturing under customer service level constraints. The problem is a stochastic extension of the classical lot sizing problem where demand can be met via two alternative sources: manufacturing new products and remanufacturing returned products. It is known that even the deterministic version of this problem is NP-hard. We propose a mixed integer programming based heuristic for the problem building on a static-dynamic uncertainty strategy.
In operational control of hybrid systems, control objectives often change with current operating conditions and switching among a number of control strategies is then inevitable. The proposed softly switched hybrid pr...
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In operational control of hybrid systems, control objectives often change with current operating conditions and switching among a number of control strategies is then inevitable. The proposed softly switched hybrid predictive control utilizes mixed integer programming techniques and achieves better switching transient performance both in system output/state and control input than the traditional hard switching method. Stability of the designed soft switching process is analysed and sufficient stabilization conditions are derived. Numerical examples with simulation results show that the proposed approach can be useful in practical applications.
Hybrid Systems consist of continuous time and/or discrete time processes interfaced with some logical or decision making process. In this paper, a class of hybrid systems - switched linear systems is considered. It is...
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Hybrid Systems consist of continuous time and/or discrete time processes interfaced with some logical or decision making process. In this paper, a class of hybrid systems - switched linear systems is considered. It is shown that for this class of hybrid systems, it is possible to combine subspace methods with mixed integer programming. While most approaches are based on an input-output framework, we a state space identification approach is advocated. The states of the system are extracted from input-output data using sub-space methods. Once these states are known, the switched system is re-written as a mixed logical dynamical (MLD) system and the model parameters are solved for via mixed integer programming. An example is reported at the end of this paper.
This paper addresses the integrated flexible job shop and operators scheduling problem, introducing shift-based constraints on operators. We investigate how the advanced modeling and solution techniques, specifically,...
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This paper addresses the integrated flexible job shop and operators scheduling problem, introducing shift-based constraints on operators. We investigate how the advanced modeling and solution techniques, specifically, mixed-integerprogramming (MIP) and Constraint programming (CP) perform on this intricate scheduling problem. We test the effectiveness of both the MIP and CP models on an illustrative example as well as on a set of larger instances and draw conclusions, which indicate the need to integrate these two models into some approximation scheme to tackle large-scale instances for this complex problem.
The problem of data reconciliation and the detection and identification of gross errors, such as measurement bias, are closely related. This close relationship prompted the development of a technique that combines the...
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The problem of data reconciliation and the detection and identification of gross errors, such as measurement bias, are closely related. This close relationship prompted the development of a technique that combines these ideas within a mixedinteger optimization framework. This paper describes such an approach and demonstrates its performance with a challenging test problem.
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