Effect of Human Capital on Organization Performance: An Analysis from Service Sector of Punjab, Pakistan

In today’s fast changing environment, where globalization is taking place, competition is increasing day by day. So, it has become a challenge for organizations to remain competitive. In order to remain competitive, it has become necessary for organizations to find ways through which they can compete in competitive world. For this reason, human capital is such a resource that can provide organizations with competitive advantage as human capital resource cannot be easily copied or imitated. In order to find out the impact of human capital on organization performance, present study is carried out in service sector of Punjab, Pakistan. For this purpose data was collected from five major cities of Punjab, Pakistan. Respondents were faculty members of universities and officer grade employees of banking sector. Analysis showed that human capital does affect the career, job and life satisfaction of employees which are indicators of organization performance. Empirical analysis showed that human capital positively affects the career satisfaction as was shown by β = 0.500, and significant at p = 0.000. Same is case with human capital and job satisfaction as represented by β = 0.281, and significant at p = 0.000. Human Capital and life satisfaction was also found to be dependent as shown by β = 0.301, significant at p = 0.000

Effect of Human Capital on Organization Performance: An Analysis from Service Sector of Punjab, Pakistan

In today’s fast changing environment, where globalization is taking place, competition is increasing day by day. So, it has become a challenge for organizations to remain competitive. In order to remain competitive, it has become necessary for organizations to find ways through which they can compete in competitive world. For this reason, human capital is such a resource that can provide organizations with competitive advantage as human capital resource cannot be easily copied or imitated. In order to find out the impact of human capital on organization performance, present study is carried out in service sector of Punjab, Pakistan. For this purpose data was collected from five major cities of Punjab, Pakistan. Respondents were faculty members of universities and officer grade employees of banking sector. Analysis showed that human capital does affect the career, job and life satisfaction of employees which are indicators of organization performance. Empirical analysis showed that human capital positively affects the career satisfaction as was shown by β = 0.500, and significant at p = 0.000. Same is case with human capital and job satisfaction as represented by β = 0.281, and significant at p = 0.000. Human Capital and life satisfaction was also found to be dependent as shown by β = 0.301, significant at p = 0.000

External Debt and Domestic Investment in Pakistan: A Cointegration Analysis

The present study explores the impacts of foreign capital inflows in terms of external debt, foreign direct investment and worker’s remittances on domestic investment in Pakistan economy for the period of 1972-2007. Since the study utilizes the time series data of the sample period so augmented Dickey-Fuller unit root test has been employed to find out each of the time series variables to be stationary at their first difference. The Johansen cointegration confirms two cointegrating vectors and all of explanatory variables show positive and significant impact on domestic investment in long run. The Granger causality test results, based on the VECM, confirm long run and short run causality from external debt, foreign direct invest and worker’s remittances to domestic investment. The diagnostic and stability tests conclude the model to be valid and stable. The study also provides some policy recommendations. Keywords: External Debt, Investment, Remittances, Cointegration, Granger Causality

Minimising total flowtime in a no-wait flow shop (NWFS) using genetic algorithms

This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA) that is implemented in a spreadsheet environment. The GA functions as an add-in in the spreadsheet. It is demonstrated that with proposed approach any criteria can be optimised without modifying the GA routine or spreadsheet model. Furthermore, the proposed method for solving this class of problem is general purpose, as it can be easily customised by adding or removing jobs and machines. Several benchmark problems already published in the literature are used to demonstrate the problem-solving capability of the proposed approach. Benchmark problems set ranges from small (7-jobs, 7 machines) to large (100-jobs, 10-machines). The performance of the GA is compared with different meta-heuristic techniques used in earlier literature. Experimental analysis demonstrate that solutions obtained in this research offer equal quality as compared to algorithms already developed for NWFS problems

Preliminary Aircraft Design Optimization Using Genetic Algorithms

Aircraft design is a highly nonlinear problem and inherently multidisciplinary activity that involves a large number of design variables and different models and tools for various aspects of design. A spreadsheet based genetic algorithm (GA) approach is presented to optimize the preliminary design of an aircraft. A domain independent general purpose genetic algorithm is proposed to implement the optimization routine. Breguet range equation is used as the objective function for the design evaluation. A total of sixteen design variables are considered in the optimization process. It has also been demonstrated that the proposed approach can be adapted to any objective function without changing the optimization routine. The model is applicable to commercial airliner as well as a multirole jet fighter. The proposed model has been validated against known configurations of various aircraft. &nbsp

Identical parallel-machine scheduling and worker assignment problem using genetic algorithms to minimize makespan

dentical parallel machine scheduling problem for minimizing the makespan is a very important production scheduling problem which has been proven to be NP-hard. The problem further compounds with additional constraints. Genetic algorithms (GA) have shown great advantages in solving the combinatorial optimization problem in view of its characteristic that has high efficiency and that is fit for practical application. In this chapter we present a spreadsheet based GA approach for minimizing the makespan for scheduling of a set of tasks for identical parallel machines and worker assignment to machines. The results obtained from the proposed approach are compared with two sets of benchmark problems consisting of 100 problems each. It has been demonstrated that the performance of proposed approach is superior to the results that have been obtained earlier. The proposed approach produces optimal solution for almost 95% of the problems demonstrating the effectiveness of the proposed approach. An empirical analysis of GA parameters has also been carried out to see the effect on the performance of the proposed algorithm

Integrated process planning and scheduling using genetic algorithms

Projektiranje tehnoloških procesa i planiranje predstavljaju dvije najvažnije funkcije svakog proizvodnog procesa. Tradicionalno se one smatraju dvjema odvojenim funkcijama. U ovom se radu predlaže Genetički Algoritam (GA) za integraciju ovih aktivnosti, gdje se simultano odvija izbor najboljeg tehnološkog procesa i vremenski plan poslova u pogonu. U radu se za rješavanje te vrste problema predstavlja pristup zasnovan na proračunskoj tablici neovisnog područja. U modelu se razmatraju odnosi prvenstva u izvođenju poslova na temelju kojih se donosi implicitno predstavljanje mogućih planova za izvršenje svakog posla. Zbog provjere izvršenja i ostvarivosti predstavljenog pristupa, predloženi se algoritam provjeravao na nizu referentnih problema prilagođenih iz ranije objavljene literature. Eksperimentalni rezultati pokazuju da se predloženim pristupom mogu učinkoviti postići optimalna ili njima blizu rješenja za probleme prilagođene iz literature. Također je pokazano da predloženi algoritam ima opću namjenu i može se primijeniti za optimizaciju bilo koje objektivne funkcije bez promjene modela ili osnovne GA rutine.Process planning and scheduling are two of the most important functions in any manufacturing system. Traditionally process planning and scheduling are considered as two separate functions. In this paper a Genetic Algorithm (GA) for integrated process planning and scheduling is proposed where selection of the best process plan and scheduling of jobs in a job shop environment are done simultaneously. In the proposed approach a domain independent spreadsheet based approach is presented to solve this class of problems. The precedence relations among job operations are considered in the model, based on which implicit representation of a feasible process plans for each job can be done. To verify the performance and feasibility of the presented approach, the proposed algorithm has been evaluated against a number of benchmark problems that have been adapted from the previously published literature. The experimental results show that the proposed approach can efficiently achieve optimal or near-optimal solutions for the problems adopted from literature. It is also demonstrated that the proposed algorithm is of general purpose in application and could be used for the optimisation of any objective function without changing the model or the basic GA routine

A research survey: review of flexible job shop scheduling techniques

In the last 25 years, extensive research has been carried out addressing the flexible job shop scheduling (JSS) problem. A variety of techniques ranging from exact methods to hybrid techniques have been used in this research. The paper aims at presenting the development of flexible JSS and a consolidated survey of various techniques that have been employed since 1990 for problem resolution. The paper comprises evaluation of publications and research methods used in various research papers. Finally, conclusions are drawn based on performed survey results. A total of 404 distinct publications were found addressing the FJSSP. Some of the research papers presented more than one technique/algorithm to solve the problem that is categorized into 410 different applications. Selected time period of these research papers is between 1990 and February 2014. Articles were searched mainly on major databases such as SpringerLink, Science Direct, IEEE Xplore, Scopus, EBSCO, etc. and other web sources. All databases were searched for “flexible job shop” and “scheduling” in the title an