Heuristic approaches for solid transportation-p-facility location problem

Das, Soumen Kumar; Roy, Sankar Kumar; Weber, Gerhard

doi:10.1007/s10100-019-00610-7

Cited by 47 publications

(24 citation statements)

References 32 publications

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“…Many researchers have worked on optimization problems and applications of computers in order to find the best solution methods . In various kinds of research, it has been shown that closed‐loop SCND belongs to NP‐hard problems.…”

Section: Solution Methodsmentioning

confidence: 99%

“…In addition, the amounts of pledged the period t', which is saved to release in period t (t' < t), is added to the released earnings. Equation (35) denotes the amount of pledged money in period t, which cannot exceed the total income in this period. Equation (36) shows the debt balance of purchasing raw materials.…”

Section: Financial Flow Constraintsmentioning

confidence: 99%

“…Many researchers have worked on optimization problems and applications of computers in order to find the best solution methods. [33][34][35] In various kinds of research, 36,37 it has been shown that closed-loop SCND belongs to NP-hard problems. For this reason, it is necessary to apply approximate solution methods to solve the problem in large-scale cases within a reasonable computational time.…”

Section: Metaheuristic Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Goli

Zare

Tavakkoli‐Moghaddam

et al. 2019

Computational Intelligence

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This paper addresses the multiobjective, multiproducts and multiperiod closed‐loop supply chain network design with uncertain parameters, whose aim is to incorporate the financial flow as the cash flow and debts' constraints and labor employment under fuzzy uncertainty. The objectives of the proposed mathematical model are to maximize the increase in cash flow, maximize the total created jobs in the supply chain, and maximize the reliability of consumed raw materials. To encounter the fuzzy uncertainty in this model, a possibilistic programming approach is used. To solve large‐sized problems, the multiobjective simulated annealing algorithm, multiobjective gray wolf optimization, and multiobjective invasive weed optimization are proposed and developed. The numerical results demonstrate that these algorithms solve the problems within about 1% of the required solving time for the augmented ε‐constraint and have similar performance and even better in some cases. The multiobjective simulated annealing algorithm with a weak performance takes less time than the other two algorithms. The multiobjective gray wolf optimization and multiobjective invasive weed optimization algorithms are superior based on the multiobjective performance indices.

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Section: Solution Methodsmentioning

confidence: 99%

Section: Financial Flow Constraintsmentioning

confidence: 99%

Section: Metaheuristic Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Goli

Zare

Tavakkoli‐Moghaddam

et al. 2019

Computational Intelligence

View full text Add to dashboard Cite

show abstract

“…The authors have proposed to solve multi-choice multi-objective transportation problem by employing the conic scalarization approach with less number of variables and with minimum computational burden (Roy et al 2017b). Whereas Das et al (2019) they studied the solid transportation-p-facility location problem (ST-p-FLP). They presented a generalization of the classical STP in which location facility sites are sought so that the total transportation cost by means of conveyances from existing facility sites to potential facility sites will be minimized.…”

Section: A Literature Reviewmentioning

confidence: 99%

Influence of assortment allocation management in the warehouse on the human workload

Kudelska

Pawłowski

2019

Cent Eur J Oper Res

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Activities related to allocation of goods in the warehouse are crucial for logistics. All operations with goods in the warehousing area are labour-intensive and time-consuming, which in turn generates warehousing costs. Despite the ongoing automation in this area, human labour is still applicable in many warehouses. This study includes researches on impact of the assortment allocation in the warehouse on the human factor (HR). It includes the analysis for research literature concerning the warehousing and picking influence on HR in its scope, as well as simulation of goods allocation in the warehousing area and discussion concerning the obtained results. The simulation is carried out with application of the swarm algorithm, and the results were subjected to the statistical analysis. Correlation of cost optimization and factors influencing the ergonomics of operation in the warehousing area is determined.

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“…Also, Reference applied genetic algorithm to derive a series of optimal solutions to a rough matrix game. Das et al developed two heuristic approaches to solve optimum places for the facilities and optimum transportation from.…”

Section: Introductionmentioning

confidence: 99%

Employing a Gaussian Particle Swarm Optimization method for tuning Multi Input Multi Output‐fuzzy system as an integrated controller of a micro‐grid with stability analysis

Mir

Dayyani

Sutikno

et al. 2019

Computational Intelligence

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There are mainly two most essential problems in power networks, load frequency control and power flow management, which are grown recently because of growth in dimension/complication of grids. Present work suggests a controller based on fuzzy systems in which controller design is performed in a supervisory manner over a multiagent system aiming to control the frequency variation as well as generation cost minimization in the entire grid. The designing processes for low‐frequency controller (LFC) and management are mostly performed separately, which results in the disruption of both outputs. This challenge is tackled in this paper by the integration of them in the designing process. Additionally, stability guarantee is in high importance in the power systems, which is neglected in most of the related works. The Gaussian particle swarm optimization (GPSO) algorithm is applied for determining the optimal values of the decision variables, which can also guarantee the stability of the system by adopting a chaotic map by Gaussian function to balance the seeking abilities of particles that promotes the computation effectiveness without affecting the efficiency of the fuzzy controller. Then, the stability situationof the fuzzy + GPSO method is derived that guarantees a suitable global exploration and rapid convergence, with no require to gradients.

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Heuristic approaches for solid transportation-p-facility location problem

Cited by 47 publications

References 32 publications

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Influence of assortment allocation management in the warehouse on the human workload

Employing a Gaussian Particle Swarm Optimization method for tuning Multi Input Multi Output‐fuzzy system as an integrated controller of a micro‐grid with stability analysis

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