An efficient population-based simulated annealing algorithm for 0–1 knapsack problem

Moradi, Nima; Kayvanfar, Vahid; Rafiee, Majid

doi:10.1007/s00366-020-01240-3

Cited by 33 publications

(16 citation statements)

References 58 publications

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“…Nevertheless, as we already mentioned, this single parameter is not enough to understand instance difficulty. T 173-P150-R9-B6-L4-T14-C0.3 852 infeasible (24) T 173-P170-R7-B6-L5-T14-C0.3 799 infeasible (25) T 173-P150-R6-B9-L4-T14-C0.3 769 infeasible (26) T 173-P150-R5-B8-L5-T14-C0.3 734 infeasible (27) T 173-P150-R7-B6-L5-T14-C0.3 686 infeasible (28) T 173-P170-R6-B7-L5-T14-C0.3 681 infeasible (29) T 173-P170-R5-B8-L5-T14-C0. T 173-P130-R9-B6-L4-T14-C0.2 106 infeasible…”

Section: Gurobi Resultsmentioning

confidence: 99%

“…An initial session assignment is generated and submitted to a local search algorithm based on simulated annealing (SA) to improve its quality. SA [16] is a well-known metaheuristic that has been used to solve many different problems such as routing problems [17][18][19][20], symbolic regression [21], feature selection and/or hyperparameter tuning for classification algorithms [22][23][24], influence maximization on social networks [25], and many other problems [26,27]. Furthermore, SA has been implemented for solving many different scheduling problems related to machine scheduling problems [28], scheduling of relief teams in natural disasters [29], for the multiobjective job-shop problem [30], in scheduling tasks in cloud computing applications [31], among others.…”

Section: Heuristic Approachmentioning

confidence: 99%

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A Track-Based Conference Scheduling Problem

et al. 2022

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The scheduling of conferences is a challenging task that aims at creating successful conference programs that fulfill an often wide variety of requirements. In this work, we focus on the problem of generating conference programs that organize talks into tracks: subevents within the conference that are group-related talks. The main contributions of this work can be organized into three scopes: literature review, problem formulation and benchmarking, and heuristic approach. We provide a literature review of conference scheduling approaches that organizes these approaches within a timetabling problem taxonomy. We also describe the main characteristics of the conference scheduling approaches in the literature and propose a classification scheme for such works. To study the scheduling of conferences that include tracks, we introduce the definition of the track-based conference scheduling problem, a new problem that incorporates tracks in the conference program. We provide a binary integer linear programming model formulation for this problem. Our formulation considers the availability of presenters, chairs, and organizers, the avoidance of parallel tracks, and best paper sessions, among other classical constraints of conference scheduling problems. Additionally, based on our formulation, we propose a simple instance-generation procedure that we apply to generate a set of artificial instances. We complete our work by proposing a heuristic method based on the simulated annealing metaheuristic for solving the track-based conference scheduling problem. We compare the results obtained by our heuristic approach and the Gurobi solver regarding execution time and solution quality. The results show that the proposed heuristic method is a practical approach for tackling the problem as it obtains solutions in a fraction of the time required by Gurobi, while Gurobi is also unable to obtain an optimal solution in the defined time for a subset of the instances. Finally, from a general perspective, this work provides a new conference scheduling problem formulation that can be extended in the future to include other features common in conference programs. Moreover, thanks to the instance generation procedure, this formulation can be used as a benchmark for designing and comparing new solving approaches.

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Section: Gurobi Resultsmentioning

confidence: 99%

Section: Heuristic Approachmentioning

confidence: 99%

A Track-Based Conference Scheduling Problem

et al. 2022

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“…With the change of the fitness value, the crossover probability P c and the mutation probability P m will change. If trapped in a local extremum, the part of the individual with a larger fitness value will also have an increase in these two probabilities, so that the suppression of premature convergence can be achieved [26]. P c and P m are calculated as equations ( 4) and ( 5), respectively.…”

Section: Research On Theoretical Basis Andmentioning

confidence: 99%

Analysis of Transportation Network Scheduling of Maritime Silk Road and International Digital Trade Potential Based on Improved Genetic Algorithm under Digital Trade Barriers

Zhang

Pan

2022

Wireless Communications and Mobile Computing

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The purpose is to improve the ship scheduling capability of the Maritime Silk Road transportation network and advance the international digital trade capabilities along China’s Maritime Silk Road. The optimization process of ship network scheduling based on a simulated annealing- (SA-) improved genetic algorithm (GA) is studied. Then, according to the time-varying stochastic frontier gravity model, the potential of international digital trade between China and the countries on the western route of the Maritime Silk Road is analyzed. The model is simulated and verified. The results reveal that the improved GA has obvious advantages over other algorithms in the message delivery rate of the high-speed and low-speed TT Controller Area Network (TTCAN) protocol for ship control. Regardless of the external environment and the number of message nodes, the message delivery rate is above 95%, showing a high delivery rate and the best network scheduling effect. The total volume and proportion of trade between China and the countries along the western route of the Maritime Silk Road can represent a good growth trend over time, and the proportion of digital trade exports has increased from 9.75% in 2009 to 45.12% in 2020. China has great potential for the development of the countries along the Silk Road as a whole. The main contribution of the research is to construct the ship network scheduling optimization process of the GA improved by the SA and use the time-varying stochastic frontier gravity model to study the digital trade potential between China and the countries along the Maritime Silk Road. The data information management system for network dispatching of marine ships has been improved, and the optimal dispatching efficiency has been enhanced.

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“…In the field of combinatorial optimization, the 0~1 knapsack problem is a classic NP problem. Scholars at home and abroad use simulated annealing algorithms [29], particle swarm algorithm [30], genetic algorithm [31] and other algorithms to analyze and study it. This section uses the ICALO algorithm to optimize it and compares it with ALO, WALO and HALO to verify the feasibility of the ICALO algorithm in solving combinatorial problems.…”

Section: ~1 Knapsack Problemmentioning

confidence: 99%

Antlion Algorithm Based on Immune Cloning and Its Truss Optimization

2021

Preprint

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Antlion optimization algorithm has good search and development capabilities, but the influence weight of elite ant lions is reduced in the later stage of optimization, which leads to slower algorithm convergence and easy to fall into local optimization. For this purpose, an antlion optimization algorithm based on immune cloning was proposed. In the early stage, the reverse learning strategy was used to initialize the ant population. The Cauchy mutation operator was added to the elite antlion update to improve the later development ability of the algorithm; finally, the antlion was cloned and mutated with the immune clone selection algorithm to change the position and fitness value of the antlion, and further improve the algorithm's global optimization ability and convergence accuracy. 10 test functions and a 0~1 backpack were used to evaluate the optimization ability of the algorithm and applied to the size and layout optimization problems of the truss structure. The optimization effect was found to be good through the force effect diagram. It is verified that ICALO is applied to combinatorial optimization problems with faster convergence speed and higher accuracy. It provides a new method for structural optimization.This article is submitted as original content. The authors declare that they have no competing interests.

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An efficient population-based simulated annealing algorithm for 0–1 knapsack problem

Cited by 33 publications

References 58 publications

A Track-Based Conference Scheduling Problem

A Track-Based Conference Scheduling Problem

Analysis of Transportation Network Scheduling of Maritime Silk Road and International Digital Trade Potential Based on Improved Genetic Algorithm under Digital Trade Barriers

Antlion Algorithm Based on Immune Cloning and Its Truss Optimization

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