Multi-objective multi-item fuzzy inventory and production management problem involving fuzzy decision variables

被引:0
|
作者
Tadesse, Admasu [1 ,2 ,3 ]
Acharya, Srikumar [1 ,2 ,3 ]
Acharya, M. M. [1 ,2 ,3 ]
Sahoo, Manoranjan [1 ,2 ,3 ]
Belay, Berhanu [1 ,2 ,3 ]
机构
[1] Hawassa Univ, Coll Nat & Computat Sci, Dept Math, Hawassa, Ethiopia
[2] KIIT Univ, Sch Appl Sci, Dept Math, Bhubaneswar, India
[3] Debretabor Univ, Coll Nat & Computat Sci, Dept Math, Debretabor, Ethiopia
关键词
Multi-objective multi-item programming; Sustainable green supply chain; Fuzzy inventory; Trapezoidal fuzzy number; Fuzzy expected value; Fuzzy decision variables; PROGRAMMING APPROACH; SUPPLY CHAIN; EOQ MODEL; OPTIMALITY; CRITERIA; COST;
D O I
10.1007/s13198-024-02338-3
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The pressure to conserve the environment as a result of global warming cannot be overstated. The necessity for operational managers to devise a sustainable green inventory stems from the fact that emissions from the production and inventory process contribute extremely to global warming. This study purposes a multi-objective multi-item fuzzy inventory and production management model with green investment in order to conserve the environment. The model is formulated in such a way that all of its ordering quantities (decision variables) and some of the input parameters are fuzzified. All the decision variables and some of the input parameters respectively are trapezoidal fuzzy decision variable and trapezoidal fuzzy number. The developed multi-objective model contains five objectives such as maximizing profit, minimizing total back-ordered quantity, minimizing the holding cost in the system, minimizing total waste produced by the inventory system per cycle and minimizing the total penalty cost due to green investment. Budget constraints, space restrictions, cost constraint on ordering each item, environmental waste disposal restrictions, pollution control costs, electricity consumption costs during production, and green house gas emission costs are among the restraints. To determine the crisp equivalent of this fuzzy model, an expected value method of defuzzification is used. The lexicographic method is applied on the resulting crisp mathematical model to find the compromise solutions. The methodology is demonstrated using a case study and the solution obtained provides a beneficial recommendation to industrial decision-makers.
引用
收藏
页码:3306 / 3317
页数:12
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