Pareto-optimal solution for multiple objective linear programming problems with fuzzy goals

Wu, Yan-Kuen; Liu, Chia-Cheng; Lur, Yung-Yih

doi:10.1007/s10700-014-9192-2

Cited by 22 publications

(15 citation statements)

References 26 publications

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“…A decision plan x 0 ∈ X is said to be a Pareto-optimal solution to the multiple objective optimization problem if no other y ∈ X, exists, such that f k (y) ≤ f k (x 0 ) for all k and f s (y) < f s (x 0 ) for at least one s (Wu et al [49]).…”

Section: Definitionmentioning

confidence: 99%

“…However, Jimenez and Bilbao [48] proved that a fuzzy-efficient solution might not always be a Pareto-optimal solution. Therefore, Wu et al [49] recently modified the method of Jimenez and Bilbao [48] for ensuring the Pareto-optimal solution by redefining membership functions in fuzzy environments. The authors proved that the solution methodology guarantees a Pareto-optimal solution with additional robust information for decision makers and is easy to implement.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Human Resource Allocation Approach for Sustainable Traffic Management

Sanyal

Nielsen

Saha

2020

IJERPH

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Efficient human resource deployment is one of the key aspects of road traffic management for maintaining the lifelines of any metropolitan city. The problem becomes relevant when collaboration between human resources with different skills in day-to-day operations is necessary to maintain public and commercial transport, manage various social events and emergency situations, and hence reduce congestion, injuries, emissions, etc. This study proposes a two-phase fuzzy multi-objective binary programming model for optimal allocation of five different categories of human resources to minimize the overall operational cost, maximize the allocation to accident-prone road segments, minimize the number of volunteer personnel and maximize the direct contact to reduce emissions and road traffic violations, simultaneously. A binary programming model is formulated to provide an efficient individual manpower allocation schedule for multiple road segments at different shifts. A case study is proposed for model evaluation and to derive managerial implications. The proposed model can be used to draw insights into human resource allocation planning in traffic management to reduce road traffic congestion, injuries and vehicular emissions.

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Section: Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Objective Human Resource Allocation Approach for Sustainable Traffic Management

Sanyal

Nielsen

Saha

2020

IJERPH

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“…A two-phase approach [36] is used to obtain a fuzzy efficient solution. The following are several useful definitions for the context.…”

Section: Solution Proceduresmentioning

confidence: 99%

“…In these circumstances, fuzzy-efficiency does not guarantee Pareto optimality. Because the proposed production-distribution planning problem contains imprecise raw material resources (Constraints (7)), we use the two-phase approach proposed by Wu et al [36]. If we assume that M st has the minimum resource M L r with tolerance t r (r = 1, 2, .…”

Section: Solution Proceduresmentioning

confidence: 99%

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Fuzzy Bi-Objective Production-Distribution Planning Problem under the Carbon Emission Constraint

2016

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This study addresses the design of a four-stage production distribution system under a carbon emission constraint. The first stage contains a set of established retail outlets. The second stage consists of a set of possible distribution centers. The third stage is comprised of a set of manufacturing units. The final and fourth stage involves a set of suppliers. We propose a bi-objective optimization problem with a mixed-integer linear programming scheme for maximizing the total profits while minimizing the cumulative shortages in a multi-period planning horizon with inaccurate information on raw material resources. We also propose a two-phase approach to solve the proposed model and obtain a Pareto-optimal solution. The effectiveness of the solution method for obtaining the fuzzy efficient solution is demonstrated with computational experiments. Sensitivity analysis is used for examining the effect of the carbon emission constraint on the optimal decisions.

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Optimization of Multi-objective Stochastic Linear Programming Problem in Fuzzy Environment: An Iterative-Interactive Optimization Process

Garai¹,

Chowdhury

Biswas

et al. 2020

Recent Advances in Intelligent Information Systems and Applied Mathematics

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Pareto-optimal solution for multiple objective linear programming problems with fuzzy goals

Cited by 22 publications

References 26 publications

Multi-Objective Human Resource Allocation Approach for Sustainable Traffic Management

Multi-Objective Human Resource Allocation Approach for Sustainable Traffic Management

Fuzzy Bi-Objective Production-Distribution Planning Problem under the Carbon Emission Constraint

Optimization of Multi-objective Stochastic Linear Programming Problem in Fuzzy Environment: An Iterative-Interactive Optimization Process

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