http://web.nchu.edu.tw/pweb/users/arborfish/lesson/8682.pdf

A survey of variants and extensions of the resource-constrained project scheduling problem

In this paper recent developments in the estimation of frontier functions and the measurement of efficiency are surveyed, and the potential applicability of these methods in agricultural economics is discussed. Frontier production, cost and profit functions are discussed, along with the construction of technical, allocative, scale and overall efficiency measures relative to these estimated frontiers. The two primary methods of frontier estimation, econometric and linear programming, are compared. A survey of recent applications of frontier methods in agriculture is also provided. (This abstract was borrowed from another version of this item.)

Recent Developments in Frontier Modelling and Efficiency Measurement

Personnel scheduling: A literature review

We consider heuristic algorithms for the resource-constrained project scheduling problem. Starting with a literature survey, we summarize the basic components of heuristic approaches. We briefly describe so-called X -pass methods which are based on priority rules as well as metaheuristic algorithms. Subsequently, we present the results of our in-depth computational study. Here, we evaluate the performance of several state-of-the-art heuristics from the literature on the basis of a standard set of test instances and point out to the most promising procedures. Moreover, we analyze the behavior of the heuristics with respect to their components such as priority rules and metaheuristic strategy. Finally, we examine the impact of problem characteristics such as project size and resource scarceness on the performance.

Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem

https://www.uv.es/rmarti/paper/docs/ss8.pdf

Principles of scatter search

An evaluation of the adequacy of project network generators with systematically sampled networks

The efficient and effective management of nursing personnel is of critical importance in a hospital's environment comprising a vast share of the operational costs. The adopted nurse workforce practices and policies highly affect the nurses' working conditions and the provided quality of care. Policy decisions on the staffing level have an impact on the outcome of the scheduling level and vice versa. Isolated reasoning typically leads to suboptimal decisions often resulting in ineffective outcomes of care. In order to overcome these inefficiencies, we propose in this paper a new integrative nurse staffing and shift scheduling approach. We test and assess the benefits of our approach in a reallife environment. Moreover, we examine the impact of several personnel policies on the staffing decision.

An integrated nurse staffing and scheduling analysis for longer-term nursing staff allocation problems

The efficient management of nursing personnel is of critical importance in a hospital's environment comprising a vast share of the hospital's operational costs. The nurse scheduling process affects highly the nurses' working conditions, which are strongly related to the provided quality of care. In this paper, we consider the rostering over a mid-term period that involves the construction of duty timetables for a set of heterogeneous nurses. In scheduling nursing personnel, the head nurse is typically confronted with various (conflicting) goals complying with different priority levels which represent the hospital's policies and the nurses' preferences. In constructing a nurse roster, nurses need to be assigned to shifts in order to maximize the quality of the constructed timetable satisfying the case-specific time related constraints imposed on the individual nurse schedules. Personnel rostering in healthcare institutions is a highly constrained and difficult problem to solve and is known to be NP-hard. In this paper, we present an exact branch-and-price algorithm for solving the nurse scheduling problem incorporating multiple objectives and discuss different branching and pruning strategies. Detailed computational results are presented comparing the proposed branching strategies and indicating the beneficial effect of various principles encouraging computational efficiency.

Branching strategies in a branch-and-price approach for a multiple objective nurse scheduling problem

In this paper, we present a novel meta-heuristic technique for the nurse scheduling problem (NSP). This well-known scheduling problem assigns nurses to shifts per day maximizing the overall quality of the roster while taking various constraints into account. The problem is known to be NP-hard. 

Due to its complexity and relevance, many algorithms have been developed to solve practical and often case-specific models of the NSP. The huge variety of constraints and the several objective function possibilities have led to exact and meta-heuristic procedures in various guises, and hence comparison and state-of-the-art reporting of standard results seem to be a utopian idea. 

We present a meta-heuristic procedure for the NSP based on the framework proposed by Birbil and Fang (J. Glob. Opt. 25, 263---282, 2003). The Electromagnetic (EM) approach is based on the theory of physics, and simulates attraction and repulsion of sample points in order to move towards a promising solution. Moreover, we present computational experiments on a standard benchmark dataset, and solve problem instances under different assumptions. We show that the proposed procedure performs consistently well under many different circumstances, and hence, can be considered as robust against case-specific constraints.

Broos Maenhout

Papers

An evaluation of the adequacy of project network generators with systematically sampled networks

An integrated nurse staffing and scheduling analysis for longer-term nursing staff allocation problems

Branching strategies in a branch-and-price approach for a multiple objective nurse scheduling problem

An electromagnetic meta-heuristic for the nurse scheduling problem

A hybrid scatter search heuristic for personalized crew rostering in the airline industry