A binary multiple knapsack model for single machine scheduling with machine unavailability

Laalaoui, Yacine; M’Hallah, Rym

doi:10.1016/j.cor.2016.02.005

Cited by 28 publications

(7 citation statements)

References 51 publications

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“…They consider assignment to a base station of cell phone users. With a help of MKP can be modeled production planing with machine failures [28,29]. In Reference [30], algorithmic approaches to the MKP are discussed.…”

Section: Multiple-constraint Knapsack Problemmentioning

confidence: 99%

ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Fidanova

Atanassov

2021

Mathematics

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Some of industrial and real life problems are difficult to be solved by traditional methods, because they need exponential number of calculations. As an example, we can mention decision-making problems. They can be defined as optimization problems. Ant Colony Optimization (ACO) is between the best methods, that solves combinatorial optimization problems. The method mimics behavior of the ants in the nature, when they look for a food. One of the algorithm parameters is called pheromone, and it is updated every iteration according quality of the achieved solutions. The intuitionistic fuzzy (propositional) logic was introduced as an extension of Zadeh’s fuzzy logic. In it, each proposition is estimated by two values: degree of validity and degree of non-validity. In this paper, we propose two variants of intuitionistic fuzzy pheromone updating. We apply our ideas on Multiple-Constraint Knapsack Problem (MKP) and compare achieved results with traditional ACO.

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Section: Multiple-constraint Knapsack Problemmentioning

confidence: 99%

ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Fidanova

Atanassov

2021

Mathematics

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“…Laalaoui and 'Hallah used a two-phase heuristic algorithm and tried to maximize the weighted number of a single machine environment subject to scheduled maintenance periods and a common due date. They showed that the problem was strongly NP-hard, and to solve small-sized instances binary multiple knapsacks were proposed [10]. Similarly, Detti et al addressed a problem arising in a manufacturing environment concerning the joint scheduling of multiple jobs [11].…”

Section: Literature Reviementioning

confidence: 99%

An Exact Method and Ant Colony Optimization for Single Machine Scheduling Problem With Time Window Periodic Maintenance

et al. 2020

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This paper considers a time window periodic maintenance strategy with different duration windows and job scheduling activities in a single machine environment. The aim is to minimize the number of tardy jobs through the integration of production scheduling and periodic maintenance intervals. A mixedinteger linear programming model (MILP) is proposed to optimize small-sized test instances. Furthermore, an ant colony optimization (ACO) algorithm is developed to solve larger sized test instances. Subsequently, to measure the efficiency of the solutions obtained by ACO, Moore's algorithm is also developed to benchmark with ACO. To test the efficiency and the effectiveness of the ACO algorithm, a set of data for small and large sized problems was generated in which several parameters were adopted and then ten replicates were solved for each combination. The small sized instances were solved by the MILP. Then, the results obtained showed that the proposed ACO was able to obtain the exact solutions within reasonable CPU times, thus, it outperformed the CPLEX solver with respect to CPU. The large sized instances were solved by the Moore's algorithm and compared to ACO. Then, the results obtained showed that the ACO outperforms Moore's algorithm for all the instances tested. It can be concluded that the developed ACOis very efficient and effective in solving the problem considered in this paper. INDEX TERMS Scheduling, MILP, single machine, periodic Maintenance, ant colony. AHMED BADWELAN received the B.Sc. degree in mechanical engineering from the Faculty of Engineering, University of Aden, in 2012, and the M.S. degree in industrial engineering from King Saud University, Saudi Arabia. He is currently pursuing the Ph.D. degree with the

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“…Laalaoui [34] experimented two swap heuristics to improve on the solutions produced by MTHM. The approach was later extended by Laalaoui and M'Hallah [35], who proposed a variable neighborhood search that makes use of a linked list data structure and a dynamic threshold acceptance criterion. They computationally tested their algorithm on instances with up to 4800 items and 2400 knapsacks, obtaining state of the art results improving both on MTHM and the genetic algorithms by Fukunaga [22].…”

Section: Heuristicsmentioning

confidence: 99%

Mathematical models and decomposition methods for the multiple knapsack problem

Dell’Amico

Delorme

Iori

et al. 2019

European Journal of Operational Research

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We consider the multiple knapsack problem, that calls for the optimal assignment of a set of items, each having a profit and a weight, to a set of knapsacks, each having a maximum capacity. The problem has relevant managerial implications and is known to be very difficult to solve in practice for instances of realistic size. We review the main results from the literature, including a classical mathematical model and a number of improvement techniques. We then present two new pseudo-polynomial formulations, together with specifically tailored decomposition algorithms to tackle the practical difficulty of the problem. Extensive computational experiments show the effectiveness of the proposed approaches.

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A binary multiple knapsack model for single machine scheduling with machine unavailability

Cited by 28 publications

References 51 publications

ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

An Exact Method and Ant Colony Optimization for Single Machine Scheduling Problem With Time Window Periodic Maintenance

Mathematical models and decomposition methods for the multiple knapsack problem

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