http://www3.eng.cam.ac.uk/~hj231/Papers/rostering.pdf

Staff scheduling and rostering: A review of applications, methods and models

Introduction. Fundamentals of Fuzzy Set Theory. Fuzzy Linear Programming. Fuzzy Nonlinear Programming. Interactive Multiobjective Linear Programming with Fuzzy Parameters. Interactive Multiobjective Nonlinear Programming with Fuzzy Parameters. Interactive Computer Programs. Some Applications. Further Research Directions. Index.

Fuzzy sets and interactive multiobjective optimization

Operations managers and scholars in their search for fast and good solutions to real-world problems have applied genetic algorithms to many problems. While genetic algorithms are promising tools for problem solving, future research will benefit from a review of the problems that have been solved and the designs of the genetic algorithms used to solve them. This paper provides a review of the use of genetic algorithms to solve operations problems. Reviewed papers are classified according to the problems they solve. The basic design of each genetic algorithm is described, the shortcomings of the current research are discussed and directions for future research are suggested.

Use of genetic algorithms to solve production and operations management problems: A review

Over the last decade, there has been a rapid growth of the use of genetic algorithms in the various areas of production and operations management. This paper provides a review of genetic algorithms research published in twenty-one major production and operations management journals from 1990–2001. More specifically, it identifies research trends and publication outlets of genetic algorithms applications. Our findings show that there are only a handful of production and operations management areas to which genetic algorithms have been applied as the solution approach. Furthermore, we recognize and discuss potential research areas and outlets in which researchers may target their work as well as the need for top ranked POM journals to consider publishing genetic algorithms related papers.

Application of genetic algorithms in production and operations management: a review

Display Omitted An improved fruit fly optimization algorithm (IFFOA) for solving the multidimensional knapsack problem (MKP) is proposed.The parallel search is employed to balance exploitation and exploration.A modified harmony search algorithm (MHS) is presented to add cooperation among swarms in IFFOA.A novel vertical crossover is designed to guide stagnant dimensions out of local optima.Experimental results indicate that IFFOA is an effective alternative for solving the MKP. This paper presents an improved fruit fly optimization algorithm (IFFOA) for solving the multidimensional knapsack problem (MKP). In IFFOA, the parallel search is employed to balance exploitation and exploration. To make full use of swarm intelligence, a modified harmony search algorithm (MHS) is proposed and applied to add cooperation among swarms in IFFOA. In MHS, novel pitch adjustment scheme and random selection rule are developed by considering specific characters of MKP and FOA. Moreover, a vertical crossover is designed to guide stagnant dimensions out of local optima and further improve the performance. Extensive numerical simulations are conducted and comparisons with other state-of-the-art algorithms verify that the proposed algorithm is an effective alternative for solving the MKP.

An improved fruit fly optimization algorithm for solving the multidimensional knapsack problem

A fuzzy programming approach to multiobjective multidimensional 0–1 knapsack problems

/pdf/application-of-genetic-annealing-to-a-fuzzy-manpower-5d45d6c08o.pdf

Application of Genetic Annealing to a Fuzzy Manpower Allocation Problem

In this paper, we present a metaheuristic solution method for a simulation based on a real world manpower allocation problem. The problem includes 7,095 0-1 variables making stochastic algorithms the most viable strategy. A fuzzy model was used to represent and deal with the multiple objectives expressed in linguistic terms by the decision maker. The mutate and spread metaheuristic, that is used in this paper, keeps a diversified population where only a good solution building blocks are permitted to spread.

Fuzzy manpower allocation using the mutate and spread metaheuristic

Manpower allocation using genetic annealing

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Papers

A fuzzy programming approach to multiobjective multidimensional 0–1 knapsack problems

Application of Genetic Annealing to a Fuzzy Manpower Allocation Problem

Fuzzy manpower allocation using the mutate and spread metaheuristic

Manpower allocation using genetic annealing