Nysret Musliu

Efficient generation of rotating workforce schedules

Generating high-quality schedules for a rotating workforce is a critical task in all situations where a certain staffing level must be guaranteed, such as in industrial plants or police departments. Results from ergonomics (BEST, Guidelines for shiftworkers, Bulletin of European Time Studies No. 3, European Foundation for the Improvement of Living and Working Conditions, 1991) indicate that rotating workforce schedules have a profound impact on the health and satisfaction of employees as well as on their performance at work. Moreover, rotating workforce schedules must satisfy legal requirements and should also meet the objectives of the employing organization. In this paper, our description of a solution to this problem is being stated. One of the basic design decisions was to aim at high-quality schedules for realistically sized problems obtained rather quickly, while maintaining human control. The interaction between the decision-maker and the algorithm therefore consists of four steps: (1) choosing a set of lengths of work blocks (a work block is a sequence of consecutive days of work), (2) choosing a particular sequence of blocks of work and days-off blocks amongst these that have optimal weekend characteristics, (3) enumerating possible shift sequences for the chosen work blocks subject to shift change constraints and bounds on sequences of shifts, and (4) assignment of shift sequences to work blocks while fulfilling the staffing requirements. The combination of constraint satisfaction and problem-oriented intelligent backtracking algorithms in each of the four steps allows for finding good solutions for real-world problems in acceptable time. Computational results from a benchmark example found in the literature confirmed the viability of our approach. The algorithms have been implemented in commercial shift scheduling software.

Local search for shift design

Abstract Designing shifts is one of the important stages in the general workforce scheduling process. In this paper we consider solving the shift design problem by using local search methods. First we propose a set of move types that give rise to a composite neighbourhood relation. In the move selection process, we make use of the basic prohibition mechanisms of tabu search. In addition, in order to avoid having to explore the whole neighbourhood which could be prohibitively large, we evaluate the moves in decreasing order of their promise to yield some improvement. Furthermore, we propose an algorithm for generating a good initial solution, which also exploits knowledge about requirements and shift structure. Experimental results on both real-life and randomly-generated instances show the advantages of these ingredients. The solver is part of a commercial product and has shown to work well in practical cases.

Hypertree decompositions: structure, algorithms, and applications

We review the concepts of hypertree decomposition and hypertree width from a graph theoretical perspective and report on a number of recent results related to these concepts. We also show – as a new result – that computing hypertree decompositions is fixed-parameter intractable.

Heuristic Methods for Hypertree Decomposition

The literature provides several structural decomposition methods for identifying tractable subclasses of the constraint satisfaction problem. Generalized hypertree decompositionis the most general of such decomposition methods. Although the relationship to other structural decomposition methods has been thoroughly investigated, only little research has been done on efficient algorithms for computing generalized hypertree decompositions. In this paper we propose new heuristic algorithms for the construction of generalized hypertree decompositions. We evaluate and compare our approaches experimentally on both industrial and academic benchmark instances. Our experiments show that our algorithms improve previous heuristic approaches for this problem significantly.

Local search algorithm for unicost set covering problem

The unicost set covering problem is a NP-hard and it has many applications. In this paper we propose a new algorithm based on local search for solving the unicost set covering problem. A fitness function is proposed for this problem and different neighborhood relations are considered for the exploration of the neighborhood of the current solution. A new approach is introduced for effective exploration of the neighborhood during the improvement phase. This approach is based on the upper bound of the best cover, which is found during the search, and using only determined moves. Additionally, in order to avoid cycles during the search, a search history is used. The proposed algorithm is experimentally evaluated for 85 well-known random and combinatorial problems in the literature, and it gives very satisfactory results in a reasonable amount of time. The proposed algorithm improves the best existing solutions for 8 problems in the literature. For a class of combinatorial problems, the best existing results are improved significantly.

XHSTT: an XML archive for high school timetabling problems in different countries

We present the progress on the benchmarking project for high school timetabling that was introduced at PATAT 2008. In particular, we announce the High School Timetabling Archive XHSTT-2011 with 21 instances from 8 countries and an evaluator capable of checking the syntax of instances and evaluating the solutions.

A Tabu Search approach for Multi Constrained Team Orienteering Problem and its application in touristic trip planning

The touristic trip planning problem can be considered as a Multi Constrained Team Orienteering Problem with Time Windows (MCTOPTW). The MCTOPTW is characterized with a set of points of interest (POI), each having a score, a time window and some attributes such as the type or entry fee. The maximum number of POIs of certain types that can be included into the itinerary is limited. A tourist can visit the POIs during their respective time windows. The objective is to visit the points that have the highest scores during specified periods of time. This paper proposes a Tabu Search approach for solving the MCTOPTW problem. To explore the neighborhood the moves Insert, Replace and Swap are applied. Additionally, the algorithm employs a tabu list, a perturbation and a diversification mechanism. The algorithm is evaluated on benchmark instances from the literature and its performance is compared to the state of the art results.

An AI-Based Break-Scheduling System for Supervisory Personnel

Designing shift plans represents a difficult but interesting task because they must satisfy various, often conflicting, requirements. In this article, we address a complex real-world break-scheduling problem for supervisory personnel and present a scheduling system that can help professional planners create high-quality shift plans. Supervisory personnel spend most of their workday in front of computer monitors, addressing critical and constantly changing situations. For employees working under such conditions to always maintain high levels of concentration, its essential that they take occasional breaks. Usually, the amount of break time, as well as the position and duration of breaks within their work time (shift) are regulated by labor rules that must be satisfied by a feasible shift plan. Moreover, to guarantee effective supervision, a minimum number of employees must be working at any given time.

Algorithm Selection for the Graph Coloring Problem

We present an automated algorithm selection method based on machine learning for the graph coloring problem GCP. For this purpose, we identify