Ant colony system based approach to single machine scheduling problems: weighted tardiness scheduling problem

The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.

Solving MPCC problem with the hyperbolic penalty function

The main goal of this work is to solve mathematical program with complementarity constraints (MPCC) using nonlinear programming techniques (NLP). An hyperbolic penalty function is used to solve MPCC problems by including the complementarity constraints in the penalty term. This penalty function [1] is twice continuously differentiable and combines features of both exterior and interior penalty methods. A set of AMPL problems from MacMPEC [2] are tested and a comparative study is performed.

Solving a signalized traffic intersection problem with an hyperbolic penalty function

Mathematical Program with Complementarity Constraints (MPCC) finds many applications in fields such as engineering design, economic equilibrium and mathematical programming theory itself. A queueing system model resulting from a single signalized intersection regulated by pre-timed control in traffic network is considered. The model is formulated as an MPCC problem. A MATLAB implementation based on an hyperbolic penalty function is used to solve this practical problem, computing the total average waiting time of the vehicles in all queues and the green split allocation. The problem was codified in AMPL.

Factores de rentabilização do processo de serragem de granitos com engenhos multi-lâminas

Este trabalho visa apresentar um enquadramento da realidade económica e industrial do sector transformador de granitos ornamentais em Portugal e fazer uma análise do processo de serragem, com engenhos multi-lâminas e granalha de aço, na medida em que este é o método de seccionamento de blocos de granito mais utilizado pelas grandes indústrias do sector. Tendo em conta a importância económica desta operação produtiva na indústria em causa, foi definido como fito deste projecto a análise estatística dos custos de produção; a definição de fórmulas de cálculo que permitam prever o custo médio de serragem; e o estudo de soluções economicamente viáveis e ambientalmente sustentáveis para o problema das lamas resultantes do expurgo dos engenhos. Para a persecução deste projecto foi realizada uma recolha de dados implementando rotinas de controlo e registo dos mesmos, em quadros de produção normalizados e de fácil preenchimento, pelos operadores destes equipamentos. Esta recolha de dados permitiu isolar, quantificar e formular os factores de rentabilização do processo de serragem selecionando, dentro da amostra de estudo obtida, um conjunto de serragens com características similares e com valores próximos dos valores da média estatística. Apartir dos dados destas serragens foram geradas curvas de tendência polinomial com as quais se analisaram as variações provocadas no custo médio de serragem, pelas variações do factor em estudo. A formulação dos factores de rentabilização e os dados estatísticos obtidos permitiram depois o desenvolvimento de fórmulas de cálculo do custo médio de serragem que establecem o custo de produção diferenciado em função das espessuras com, ou sem, a incorporação dos factores de rentabilização. Como consequência do projecto realizado obteve-se um conjunto de conclusões util, para o sector industrial em causa, que evidencia a importancia da Ocupação dos engenhos e rentabilização de um espaço confinado, da Resistência oferecida à serragem pelos granitos, e da Diferença de altura entre os blocos de uma mesma carga, nos custos de transformação.

A new MILP based approach for unit commitment in power production planning

This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

New insights on integer-programming models for the kidney exchange problem

In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient–donor pairs. These policies lead to what is commonly known as kidney exchange programs. The underlying optimization problems can be formulated as integer programming models. Previously proposed models for kidney exchange programs have exponential numbers of constraints or variables, which makes them fairly difficult to solve when the problem size is large. In this work we propose two compact formulations for the problem, explain how these formulations can be adapted to address some problem variants, and provide results on the dominance of some models over others. Finally we present a systematic comparison between our models and two previously proposed ones via thorough computational analysis. Results show that compact formulations have advantages over non-compact ones when the problem size is large.

Two protocols without periodicity for the global and preemptive scheduling problem of multi-mode real-time systems upon multiprocessor Platforms

We consider the problem of scheduling a multi-mode real-time system upon identical multiprocessor platforms. Since it is a multi-mode system, the system can change from one mode to another such that the current task set is replaced with a new task set. Ensuring that deadlines are met requires not only that a schedulability test is performed on tasks in each mode but also that (i) a protocol for transitioning from one mode to another is specified and (ii) a schedulability test for each transition is performed. We propose two protocols which ensure that all the expected requirements are met during every transition between every pair of operating modes of the system. Moreover, we prove the correctness of our proposed algorithms by extending the theory about the makespan determination problem.

A genetic algorithm for the resource constrained multi-project scheduling problem

This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

Adaptive tackling of the swinging problem for a 2 DOF crane – payload system

The control of a crane carrying its payload by an elastic string corresponds to a task in which precise, indirect control of a subsystem dynamically coupled to a directly controllable subsystem is needed. This task is interesting since the coupled degree of freedom has little damping and it is apt to keep swinging accordingly. The traditional approaches apply the input shaping technology to assist the human operator responsible for the manipulation task. In the present paper a novel adaptive approach applying fixed point transformations based iterations having local basin of attraction is proposed to simultaneously tackle the problems originating from the imprecise dynamic model available for the system to be controlled and the swinging problem, too. The most important phenomenological properties of this approach are also discussed. The control considers the 4th time-derivative of the trajectory of the payload. The operation of the proposed control is illustrated via simulation results.

A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problem

This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

A two-level genetic algorithm for the multi-mode resource-constrained project scheduling problem

This paper presents a genetic algorithm for the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme by introducing an improvement procedure. It is evaluated the quality of the schedule and present detailed comparative computational results for the MRCPSP, which reveal that this approach is a competitive algorithm.

Reverse problem-based learning - a case study with a Braille machine

Engineering Education includes not only teaching theoretical fundamental concepts but also its verification during practical lessons in laboratories. The usual strategies to carry out this action are frequently based on Problem Based Learning, starting from a given state and proceeding forward to a target state. The possibility or the effectiveness of this procedure depends on previous states and if the present state was caused or resulted from earlier ones. This often happens in engineering education when the achieved results do not match the desired ones, e.g. when programming code is being developed or when the cause of the wrong behavior of an electronic circuit is being identified. It is thus important to also prepare students to proceed in the reverse way, i.e. given a start state generate the explanation or even the principles that underlie it. Later on, this sort of skills will be important. For instance, to a doctor making a patient?s story or to an engineer discovering the source of a malfunction. This learning methodology presents pedagogical advantages besides the enhanced preparation of students to their future work. The work presented on his document describes an automation project developed by a group of students in an engineering polytechnic school laboratory. The main objective was to improve the performance of a Braille machine. However, in a scenario of Reverse Problem-Based learning, students had first to discover and characterize the entire machine's function before being allowed (and being able) to propose a solution for the existing problem.

Aplicação de metodologias Lean ao fabrico de elevadores

Num mercado cada vez mais competitivo, torna-se fundamental para as empresas produzirem mais com menos recursos, aumentando a eficiência interna, através da otimização dos seus processos. Neste contexto aparece o Lean Manufacturing, metodologia que tem como objetivo criar valor para os stakeholders, através da eliminação de desperdício na cadeia de valor. Este projeto descreve a análise e a formulação de soluções do processo de produção de um Módulo de Serviço, produto que faz parte do sistema elétrico de um elevador. Para análise do problema utilizamos técnicas e ferramentas lean, tais como, o value stream mapping (VSM), o diagrama de processo e o diagrama de spaghetti. Para formulação do problema usamos o value stream design (VSD), a metodologia 5S, o sistema Kanban e a criação de fluxo contínuo, através do conceito takt time, do sistema Pull, da definição do processo pacemaker, da programação nivelada (Heijunka), do conceito pitch time e da caixa de nivelamento (Heijunka Box). Com este projeto pretendemos demonstrar que a implementação de um fluxo unitário de peças através da filosofia Lean Manufacturing, acrescenta qualidade ao produto, cria flexibilidade, aumenta a produtividade, liberta áreas de produção, aumenta a segurança, reduz o custo com o stock e aumenta a motivação organizacional.