System optimization by multiobjective genetic algorithms and analysis of the coupling between variables, constraints and objectives

This paper presents a methodology based on Multiobjective Genetic Algorithms (MOGA’s) for the design of electrical engineering systems. MOGA’s allow to optimize multiple heterogeneous criteria in complex systems, but also simplify couplings and sensitivity analysis by determining the evolution of design variables along the Pareto-optimal front. A rather simplified case study dealing with the optimal dimensioning of an inverter – permanent magnet motor – reducer – load association is carried out to demonstrate the interest of the approach

Labor contracts and flexibility : evidence from a labor markt reform in Spain

This paper evaluates the effects on employment, job turnover and productivity of a labor market reform in Spain that eliminated dismissal costs for fixed-term contracts. Our empirical results are based on a panel of 2356 Spanish manufacturing firms for the period 1982-1993. We postulate and estimate a dynamic labor demand model with indefinite and fixed-term labor contracts. Our estimations use data on severance payments to identify when negative changes in employment have been associated with costly dismissals. Experiments using the estimated model show important positive effects of the reform on employment (between 2.5% and 4.5%) and job turnover (between five and seven percentage points). However, its effects on productivity and the value of a firm are negligible. This contrasts with the sizeable increases in output and v3.Iue under a hypothetical reduction in firing costs for all type of contracts. Compared with this alternative reform, the introduction of temporary contracts leads to excess turnover and employment of workers with low firm-specific experience

Managing technology risk in R&D project planning: Optimal timing and parallelization of R&D activities.

An inherent characteristic of R&D projects is technological uncertainty, which may result in project failure, and time and resources spent without any tangible return. In pharmaceutical projects, for instance, stringent scientific procedures have to be followed to ensure patient safety and drug efficacy in pre-clinical and clinical tests before a medicine can be approved for production. A project consists of several stages, and may have to be terminated in any of these stages, with typically a low likelihood of success. In project planning and scheduling, this technological uncertainty has typically been ignored, and project plans are developed only for scenarios in which the project succeeds. In this paper, we examine how to schedule projects in order to maximize their expected net present value, when the project activities have a probability of failure, and where an activity's failure leads to overall project termination. We formulate the problem, show that it is NP-hard and develop a branchand- bound algorithm that allows to obtain optimal solutions. We also present polynomial-time algorithms for special cases, and present a number of managerial insights for R&D project and planning, including the advantages and disadvantages of parallelization of R&D activities in different settings.Applications; Branch-and-bound; Computational complexity; Exact algorithms programming; Integer; Pharmaceutical; Project management; Project scheduling; R&D projects analysis of algorithms; Risk industries;

Estimation of a dynamic discrete choice model of irreversible investment

In this paper we propose and estimate a dynamic structural model of fixed capital investment at the firm level. Our dataset consists of an unbalanced panel of Spanish manufacturing firms. Two important features are present in this dataset. There are periods in which firms decide not to invest and periods of large investment episodes. These empirical evidence of infrequent and lumpy investment provides evidence in favour of irreversibilities and nonconvex capital adjustment costs. We consider a dynamic discrete choice model of irreversible investment with a general specification of adjustment costs including convex and nonconvex components. We use a two stage estimation procedure. In a first stage, we obtain GMM estimates of technological parameters. In the second stage, we obtain partial maximum likelihood estimates for the adjustment cost parameters. The estimation strategy builds on the representation of conditional value functions as a computable function of conditional choice probabilities. It is in the line of structural estimation techniques which avoid the solution of the dynamic programming problem

Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms

The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of theoptimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies

Organizing the innovation process : complementarities in innovation networking

This paper contributes to the developing literature on complementarities in organizational design. We test for the existence of complementarities in the use of external networking between stages of the innovation process in a sample of UK and German manufacturing plants. Our evidence suggests some differences between the UK and Germany in terms of the optimal combination of innovation activities in which to implement external networking. Broadly, there is more evidence of complementarities in the case of Germany, with the exception of the product engineering stage. By contrast, the UK exhibits generally strong evidence of substitutability in external networking in different stages, except between the identification of new products and product design and development stages. These findings suggest that previous studies indicating strong complementarity between internal and external knowledge sources have provided only part of the picture of the strategic dilemmas facing firms

Organizing the innovation process : complementarities in innovation networking

This paper contributes to the developing literature on complementarities in organizational design. We test for the existence of complementarities in the use of external networking between stages of the innovation process in a sample of UK and German manufacturing plants. Our evidence suggests some differences between the UK and Germany in terms of the optimal combination of innovation activities in which to implement external networking. Broadly, there is more evidence of complementarities in the case of Germany, with the exception of the product engineering stage. By contrast, the UK exhibits generally strong evidence of substitutability in external networking in different stages, except between the identification of new products and product design and development stages. These findings suggest that previous studies indicating strong complementarity between internal and external knowledge sources have provided only part of the picture of the strategic dilemmas facing firms

Simulation modelling and strategic change : creating the sustainable enterprise

Peer reviewedPublisher PD