A Multi-Objective Decision Support Model for the Turkish Armed Forces Personnel Assignment System

The Turkish Armed Forces (TAF) assign more than 25,000 active duty personnel annually. TAF wants to obtain maximum utilization of its personnel by assigning the right person to the right job at the right time, To accomplish this task, decision-makers and personnel assignment staff should consider conflicting multiple objectives that create the widely known problem called personnel assignment problem . To assist in this complicated task from a quantitative perspective, a preemptive goal programming approach was used to develop an integer programming (IP) model to capture the multiple objectives flexibly and interactively. A realistic size IP problem with random data was tested for computational efficiency and analysis. The mean solution time for different instances of the problem was reasonably small. An application of the methodology in an actual assignment decision support system of any large-scale government or non-government organization has a potential to help decision-makers make better use of their personnel

Robust Assignments via Ear Decompositions and Randomized Rounding

Many real-life planning problems require making a priori decisions before all parameters of the problem have been revealed. An important special case of such problem arises in scheduling problems, where a set of tasks needs to be assigned to the available set of machines or personnel (resources), in a way that all tasks have assigned resources, and no two tasks share the same resource. In its nominal form, the resulting computational problem becomes the \emph{assignment problem} on general bipartite graphs. This paper deals with a robust variant of the assignment problem modeling situations where certain edges in the corresponding graph are \emph{vulnerable} and may become unavailable after a solution has been chosen. The goal is to choose a minimum-cost collection of edges such that if any vulnerable edge becomes unavailable, the remaining part of the solution contains an assignment of all tasks. We present approximation results and hardness proofs for this type of problems, and establish several connections to well-known concepts from matching theory, robust optimization and LP-based techniques.Comment: Full version of ICALP 2016 pape

A Scenario-based Parametric Analysis of the Army Personnel-to-assignment Matching Problem

This study aims to compare linear programming and stable marriage approaches to the personnel assignment problem under conditions of uncertainty. Robust solutions should exhibit reduced variability of solutions in the presence of one or more additional constraints or problem perturbations added to some baseline problems.Several variations of each approach are compared with respect to solution speed, solution quality as measured by officer-to-assignment preferences and solution robustness as measured by the number of assignment changes required after inducing a set of representative perturbations or constraints to an assignment instance. These side constraints represent the realistic assignment categorical priorities and limitations encountered by army assignment managers who solve this problem semiannually, and thus the synthetic instances considered herein emulate typical problem instances

Personnel shift assignment: Existence conditions and network models

The personnel scheduling problem is known to be a five-stage process in which the final stage involves the assignment of shifts to the days worked in the schedule. This paper discusses the existence conditions for both continuous and forward rotating shift assignments and heuristic network algorithms for the determination of such assignments. Results generated for a number of test problems demonstrate, first, that the network devised to search for continuous solutions produces these solutions in a high proportion of cases where such solutions are known to exist. Second, for more general problems, the algorithm is shown to be efficient in its ability to generate either continuous or rotating solutions

Optimal Personnel Deployment Strategy for Self-Perform Maintenance on Wind Farms

Wind turbine maintenance is a major cost factor and key determinant of wind farm productivity. Many companies outsource critical maintenance procedures while others perform these tasks in-house, referred to as self-perform maintenance. While expected to reduce time to profit on asset investment, self-perform requires an efficient personnel deployment strategy to implement. In this thesis, a partial solution to the optimization of wind turbine maintenance personnel team assignment is presented. A holistic framework is established, through analysis of historical work orders, for defining metrics that evaluate the performance of technicians. These metrics are further transformed into interpretable proficiency coefficients to be incorporated into an application of the team assignment problem. A case study of a large wind farm owner and operator is presented to illustrate the potential benefits and caveats of the proposed metrics and evaluation strategy. Additionally, the practicality of the data-derived metrics and proficiencies is illustrated. Key improvement strategies in data quality and metric aggregation are detailed, as well as discussion of a potential formulation of the task-to-team assignment problem, to be modeled through a standard maximin approach and solved through an integer programming technique

A genetic algorithm with composite chromosome for shift assignment of part-time employees

Personnel scheduling problems involve multiple tasks, including assigning shifts to workers. The purpose is usually to satisfy objectives and constraints arising from management, labour unions and employee preferences. The shift assignment problem is usually highly constrained and difficult to solve. The problem can be further complicated (i) if workers have mixed skills; (ii) if the start/end times of shifts are flexible; and (iii) if multiple criteria are considered when evaluating the quality of the assignment. This paper proposes a genetic algorithm using composite chromosome encoding to tackle the shift assignment problem that typically arises in retail stores, where most employees work part-time, have mixed-skills and require flexible shifts. Experiments on a number of problem instances extracted from a real-world retail store, show the effectiveness of the proposed approach in finding good-quality solutions. The computational results presented here also include a comparison with results obtained by formulating the problem as a mixed-integer linear programming model and then solving it with a commercial solver. Results show that the proposed genetic algorithm exhibits an effective and efficient performance in solving this difficult optimisation problem

Automated Ticket Routing Helpdesk Portal

This report was commissioned to deliver the understanding of the chosen Final Year Project title "Automated Ticket Routing Helpdesk Portal". The report will be segregated into four chapters which are the introduction including problem statement and objectives; literature review; methodology and conclusion. Helpdesk is a very powerful tool to assist IT users. A good helpdesk system is very crucial to assist users and also improve service by the helpdesk team. At Universiti Teknologi Petronas, we already have an existing helpdesk system. However, I have identified a problem in the system; the current system still uses manual ticket routing and assignment. Automated ticket routing and assignment stop manually assigning tickets to the support personnel that you think is available and has the skill set to address the ticket. Automated ticket routing and assignment uses intelligent business logic to determine which support personnel is assigned to a new ticket using a combination of skill-set, work schedule and work load balancing criteria. In the introduction, problem statements that lead to the idea of developing the project title will be cleared up and the objectives are highlighted. Towards the development of this project, information gathering from the experts will be conducted. A comprehensive research also will determine the relevancy of this project. The literature reviews will explain in depth the understanding of the proposed project

A constraint model for a cyclic time personnel routing and scheduling problem

We present a crew scheduling problem with time windows in the context of scheduling train personnel, which encompasses not only assignment of resources to tasks but also the introduction of extra tasks, passive journeys, depending on the problem instance. The representation of the problem is made as a constraint program, which relies heavily on some global constraints, notably a constraint for expressing non-overlap between rectangles on a surface. A search algorithm is described and we also point out some problems and deficiencies of the current model and its computational behaviour

Optimasi Penugasan Pekerja Menggunakan Metode Hungarian Modifikasi pada Proyek Pembangunan Jembatan X di Kabupaten Timor Tengah Utara

Assignment problems that are often encountered in local life are problems related to the optimal allocation of various productive resources or personnel that have different levels of efficiency for different jobs. The Hungarian method can be used to solve balanced assignment problems, namely the number of workers is equal to the number of jobs and unbalanced assignments, and namely the number of workers is not the same as the number of jobs. The assignment problem in this study is an unbalanced assignment problem where the number of workers is 90 (ninety) people divided into 4 (four) work teams while the number of work items is as much as 7 (seven) work items. This assignment can be completed by applying a modified Hungarian method with the aim of minimizing work completion time, worker wages and minimizing completion time and worker wages together. From the research results, after using the modified Hungarian method, the optimal total time is 25 days with the optimal total cost of IDR 57,080,000 and the combined completion time and total wages calculated jointly is 87.3