This thesis deals with the issue of human resource management and it is focused on a general description of HR processes of recruitment and selection of staff. It also captures the essence of the recruitment and selection of employees, and identifies conditions that must be observed for making this system is effective. The thesis is divided into two parts. In the first, theoretical part, there are defined the keywords and described the processes and methods of recruitment and selection of employees. In the second, the practical part, there is introduced company X, the structure of its employees and the system of recruitment and selection of employees, which is established in the company. The system is at this place analyzed and compared with the generally accepted theoretical principles. With the questionnaire survey there is also examined satisfaction of employees with the company's process of recruitment and selection of staff. In conclusion of the thesis, the system of recruitment and selection of employees is appraised and there are highlighted its strengths and proposed measures for its improvement.

Försvarsmakten står inför en spännande utmaning genom att för första gången på mycket länge öka sin förmåga, med tillväxt av såväl numerära förband som förmågebredd och effekt. För att lyckas med detta är personalen en viktig komponent, kanske till och med den allra viktigaste. Det finns en stark politisk vilja att Försvarsmakten skall stärkas för att med bredare kompetens stå bättre rustad i hanteringen av en komplex hotbild. För att lyckas med en omfattande tillväxt kommer det kräva att Försvarsmakten kan behålla erfarenhet som finns inom organisationen samtidigt som det rekryteras ny personal. Denna undersökning är kvalitativ till sin utformning och fokuserar på att försöka förstå varför officerare vid K 3 väljer att söka alternativa karriärvägar. Den bygger i huvudsak på empiri från officerare som har slutat vid förbandet de tre senaste åren. Undersökningen handlar om relationen mellan en organisation och de individer som är en del av den. Resultatet visar att de huvudsakliga faktorerna till att officerare väljer alternativa karriärvägar och slutar vid förbandet handlar om att de inte tydligt kan se sina karriär- och utvecklingsmöjligheter samt bristande kommunikation avseende dessa. Individen upplever vidare en minskad samhörighet inom förbandet och att deras erfarenhet och kompetens inte omhändertas i tillräcklig omfattning.

Att bygga upp en större Försvarsmakt omfattar både utveckling och återetablering av förband. Detta medför påtagliga utmaningar utifrån rådande personalläge. Tillgänglighet på yrkesofficerare, i tillräcklig numerär och med relevant kompetens, kommer vara avgörande för tillväxttakten. Därtill har återinförandet av värnplikt, implementering av ett trebefälssystem och akademisering av officersutbildningen förändrat förutsättningarna för officersprofessionen. Studiens syfte är att skapa en djupare förståelse för hur personalförsörjning i praktiken påverkar förbanden och dess chefer. Vi ville studera vilka faktorer som haft störst inverkan på officersprofessionen inom ramen för tillväxten vid våra hemförband.  Semistrukturerade intervjuer genomfördes med chefer på Göta Ingenjörregemente (Ing 2) och Södra skånska regementet (P 7) för att förstå hur de hanterar tillväxten och de spänningar som den medför eller synliggör.   Under intervjuerna framkom att lösningen på tillväxtens utmaningar inte enbart handlar om personell uppfyllnad. Brister i grundläggande kunskaper och färdigheter, samt en accelererande vakanssituation, gör att det gradvis sker en kompetensurholkning.  Studien synliggör behovet av att systematisera kompetensförsörjningen i en långsiktig personalplanering på förbanden.  Av studien framgår också att mentor- och handledarskap, för unga officerare, är central för att kunna hantera behoven som tillväxten medför och för att utveckla officersprofessionen.  Det framkommer även i uppsatsen att många beslut kopplat till verksamhetsstyrningar och åtgärder inom tillväxten hanteras genom stuprörsledning. Detta leder till brister i framförhållning på förbanden och är en källa till frustration på flera ledningsnivåer.  Studiens övergripande insikt är att tillväxten, i olika grad och omfattning, påverkar personalförsörjningen och officersprofessionen. Vid de undersökta förbanden visar det sig att personalförsörjning inte är dimensionerad för att hantera en ökad mängd uppgifter i en tillväxande Försvarsmakt.

The work presented in this dissertation has been focused on exploiting the branch-and-price (BNP) method for the solution of various stochastic mixed integer programming problems (MIPs). In particular, we address the stochastic generalized assignment problem (SGAP), a hospital staff scheduling problem (HSSP), a stochastic hospital staff scheduling problem (SHSSP), and a stochastic short-term personnel planning problem (SSTPP). The BNP method has been developed in concert with the dual stabilization technique and other enhancements of this method for each of these problems. In view of an excessive number of scenarios that arise for these problems, we also implement the Monte Carlo method within the BNP scheme. The superiority of the BNP-based method over the branch-and-cut (BNC) method is demonstrated for all of these problems. The first problem that we address is the SGAP for which the processing time of a job on a machine is assumed to be stochastic. Even though the generalized assignment problem (GAP) has been solved using the BNP method, yet no study has been reported in the literature on the use of the BNP method for the solution of the SGAP. Our work has been motivated by the desire to fill this gap. We begin by showing that it is better to solve the SGAP as a stochastic program in contrast to solving it by using the expected values of the times required to process the jobs on the machines. Then, we show that the stochastic model of the SGAP is a complete recourse model — a useful property which permits the first stage decisions to produce feasible solutions for the recourse problems. We develop three BNP-based methods for the solution of the SGAP. The first of these is BNP-SGAP, which is a combination of branch-and-bound and column generation methods. The pricing problem of BNP-SGAP is separable with regard to each machine, and it is a multiple-constraint knapsack problem. The second method is BNP-SGAP implemented in concert with the dual stabilization technique (DST), and it is designated as BNPDST-SGAP. We have introduced a new DST by modifying the Boxstep method of Pigatti et al. [76]. We have shown that our method performs better than the method of Pigatti et al. [76] resulting in over two-fold savings in cpu times on average. The third method that we develop for the solution of the SGAP is BNPDST-SGAP implemented with an advanced start to obtain an initial feasible solution. We use a greedy heuristic to obtain this solution, and this heuristic is a modification of a similar method used for the knapsack problem. It relies on the information available at a node of the underlying branch-and-bound tree. We have shown that this procedure obtains an initial feasible solution, if it exists at that node. We designate this method as BNPDSTKP-SGAP. We have also developed a BNC method to solve the SGAP using CPLEX 9.0. We have compared the performances of the BNP and BNC methods on various problem instances obtained by varying the number of machines, the ratio of the number of machines to the number of jobs, the machine capacity, and the penalty cost per unit of extra resource required at each machine. Our results show that all BNP-based methods perform better than the BNC method, with the best performance obtained for BNPDSTKP-SGAP. An issue with the use of the scenario-based methods that we have employed for the solution of the SGAP is that the number of scenarios generally grows exponentially in problem parameters, which gives rise to a large-size problem. To overcome the complexity caused by the presence of a large number of scenarios for the solution of the SGAP, we introduce the use of the Monte Carlo method (MCM) within the BNP scheme. We designate this method as BNPDSTKP-SGAP with MCM. It affords the use of a small subset of scenarios at a time to estimate the "true" optimal objective function value. Replications of the subsets of scenarios are carried out until the objective function value satisfies a stopping criterion. We have established theoretical results for the use of the MCM. These pertain to determining unbiased estimates of: (i) lower and upper bounds of the "true" optimal objective function value, (ii) the "true" optimal solution, and (iii) the optimality gap. We have also provided the 100(1-ï ¡) confidence interval on the optimality gap. Our experimental investigation has shown the efficacy of using this method. It obtains almost optimal solutions, with the objective function value lying within 5% of the "true" optimal objective function value, while giving almost ten-fold savings in cpu time. Our experimentation has also revealed that an increment in the number of scenarios in each replication makes a greater impact on the quality of the solution obtained than an increment in the number of replications. We have also observed the impact of a change in the variance of a processing time distribution on cpu time. As expected, the optimal objective function value increases with increment in processing time variability. Also, by comparing the results with the expected value solution, it is observed that the greater the variability in the data, the better it is to use the stochastic program. The second problem that we study is the hospital staff scheduling problem. We address the following three versions of this problem: HSSP (General): Implementation of schedule incorporating the four principal elements, namely, surgeons, operations, operating rooms, and operation times; HSSP (Priority): Inclusion of priority for some surgeons over the other surgeons regarding the use of the facility in HSSP (General); HSSP (Pre-arranged): Implementation of a completely pre-fixed schedule for some surgeons. The consideration of priority among the surgeons mimics the reality. Our BNP method for the solution of these problems is similar to that for the SGAP except for the following: (i) a feasible solution at a node is obtained with no additional assignment, i.e., it consists of the assignments made in the preceding nodes of that node in the branch-and-bound tree; (ii) the columns with positive reduced cost are candidates for augmentation in the CGM; and (iii) a new branching variable selection strategy is introduced, which selects a fractional variable as a branching variable by fixing a value of which we enforce the largest number of variables to either 0 or 1. The priority problem is separable in surgeons. The results of our experimentation have shown the efficacy of using the BNP-based method for the solution of each HSSP as it takes advantage of the inherent structure of each of these problems. We have also compared their performances with that of the BNC method developed using CPLEX. For the formulations HSSP (General), HSSP (Priority), and HSSP (Pre-arranged), the BNP method gives better results for 22 out of 30, 29 out of 34, and 20 out 32 experiments over the BNC method, respectively. Furthermore, while the BNC method fails to obtain an optimal solution for 15 experiments, the BNP method obtains optimal solutions for all 96 experiments conducted. Thus, the BNP method consistently outperforms the BNC method for all of these problems. The third problem that we have investigated in this study is the stochastic version of the HSSP, designated as the Stochastic HSSP (SHSSP), in which the operation times are assumed to be stochastic. We have introduced a formulation for this formulation, designated as SHSSP2 (General), which allows for overlapping of schedules for surgeons and operating rooms, and also, allows for an assignment of a surgeon to perform an operation that takes less than a pre-arranged operation time, but all incurring appropriate penalty costs. A comparison of the solution of SHSSP2 (General) and its value with those obtained by using expected values (the corresponding problem is designated as Expected-SHSSP2 (General)) reveals that Expected-SHSSP2 (General) may end up with inferior and infeasible schedules. We show that the recourse model for SHSSP2 (General) is a relatively complete recourse model. Consequently, we use the Monte Carlo method (MCM) to reduce the complexity of solving SHSSP2 (General) by considering fewer scenarios. We employ the branch-and-cut (BNC) method in concert with the MCM for solving SHSSP2 (General). The solution obtained is evaluated using tolerance ratio, closeness to optimality, length of confidence interval, and cpu time. The MCM substantially reduces computational effort while producing almost optimal solutions and small confidence intervals. We have also considered a special case of SHSSP2 (General), which considers no overlapping schedules for surgeons and operating rooms and assigns exactly the same operation time for each assignment under each scenario, and designate it as SHSSP2 (Special). With this, we consider another formulation that relies on the longest operation time among all scenarios for each assignment of a surgeon to an operation in order to avoid scheduling conflicts, and we designate this problem as SHSSP (Longest). We show SHSSP (Longest) to be equivalent to deterministic HSSP, designated as HSSP (Equivalent), and we further prove it to be equivalent to SHSSP (General) in terms of the optimal objective function value and the optimal assignments of operations to surgeons. The schedule produced by HSSP (Equivalent) does not allow any overlap among the operations performed in an operating room. That is, a new operation cannot be performed if a previous operation scheduled in that room takes longer than expected. However, the schedule generated by HSSP (Equivalent) may turn out to be a conservative one, and may end up with voids due to unused resources in case an operation in an operating room is completed earlier than the longest time allowed. Nevertheless, the schedule is still a feasible one. In such a case, the schedule can be left-shifted, if possible, because the scenarios are now revealed. Moreover, such voids could be used to perform other procedures (e.g., emergency operations) that have not been considered within the scope of the SHSSP addressed here. Besides, such a schedule can provide useful guidelines to plan for resources ahead of time. The fourth problem that we have addressed in this dissertation is the stochastic short-term personnel planning problem, designated as Stochastic STPP (SSTPP). This problem arises due to the need for finding appropriate temporary contractors (workers) to perform requisite jobs. We incorporate uncertainty in processing time or amount of resource required by a contractor to perform a job. Contrary to the SGAP, the recourse model for this problem is not a relatively complete recourse model. As a result, we cannot employ a MCM method for the solution of this problem as it may give rise to an infeasible solution. The BNP method for the SSTPP employs the DST and the advanced start procedure developed for the SGAP, and due to extra constraints and presence of binary decision variables, we use the branching variable selection strategy developed for the HSSP models. Because of the distinctive properties of the SSTPP, we have introduced a new node selection strategy. We have compared the performances of the BNC-based and BNP-based methods based on the cpu time required. The BNP method outperforms the BNC method in 75% of the experiments conducted, and the BNP method is found to be quite stable with smaller variance in cpu times than those for the BNC method. It affords solution of difficult problems in smaller cpu times than those required for the BNC method. / Ph. D.

This thesis deals with the analysis of personnel work in a selected company and proposing improvement measures for any deficiencies. In the theoretical part are analyzed opinions of authors, who deal with the personnel work. Basic structure of personal work used in this thesis is creation and job analysis, personnel planning, recruitment and selection of staff, their evaluation and remuneration, deployment of staff, termination of employment, education and care for workers, relationships with employers and HR information system. In the pracical part is the analyzed company introduced at first, its business activities and history. Then the basic information about employees are meantioned, their number and changes in last five years. Organizational structure is described here too. At the end of the thesis are improvement neasures for some of the personal work.

Master´s thesis is focusing on the development of personal management of STAS - Pavel Sehnal company. First part of the thesis describes common requirements of personal management. In the second part I analyze present state of the company. The result of the thesis are suggestions, how to improve the personal management.