A Mathematical Programming Model of Decentralized Multi-Level Systems

1988 ◽  
Vol 39 (11) ◽  
pp. 1021 ◽  
Author(s):  
G. Anandalingam
2021 ◽  
Vol 11 (3) ◽  
pp. 936
Author(s):  
Pablo Viveros ◽  
Katalina González ◽  
Rodrigo Mena ◽  
Fredy Kristjanpoller ◽  
Javier Robledo

Efficiency in supply chains is critically affected by the performance of operations within warehouses. For this reason, the activities related to the disposition and management of inventories are crucial. This work addresses the multi-level storage locations assignment problem for SKU pallets, considering divisible locations in the first level to improve the picking operation and reduce the travel times associated with the routes of the cranes. A mathematical programming model is developed considering the objective of minimizing the total travel distance, and in the background, maximizing the use of storage capacity. To solve this complex problem, we consider its decomposition into four subproblems, which are solved sequentially. To evaluate the performance of the model, two analysis scenarios based on different storage strategies are proposed to evaluate both the entry and exit distance of pallets, as well as the cost associated with the movements.


2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Hai Shen ◽  
Lingyu Hu ◽  
Kin Keung Lai

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method has been extended in previous literature to consider the situation with interval input data. However, the weights associated with criteria are still subjectively assigned by decision makers. This paper develops a mathematical programming model to determine objective weights for the implementation of interval extension of TOPSIS. Our method not only takes into account the optimization of interval-valued Multiple Criteria Decision Making (MCDM) problems, but also determines the weights only based upon the data set itself. An illustrative example is performed to compare our results with that of existing literature.


2014 ◽  
Vol 13 (01) ◽  
pp. 101-135 ◽  
Author(s):  
MUKESH KUMAR MEHLAWAT ◽  
PANKAJ GUPTA

In this paper, we develop a hybrid bi-objective credibility-based fuzzy mathematical programming model for portfolio selection under fuzzy environment. To deal with imprecise parameters, we use a hybrid credibility-based approach that combines the expected value and chance constrained programming techniques. The model simultaneously maximizes the portfolio return and minimizes the portfolio risk. We also consider an additional important criterion, namely, portfolio liquidity as a constraint in the model to make it better suited for practical applications. The proposed fuzzy optimization model is solved using a two-phase approach. An empirical study is included to demonstrate applicability of the proposed model and the solution approach in real-world applications of portfolio selection.


2012 ◽  
Vol 52 (No. 2) ◽  
pp. 51-66 ◽  
Author(s):  
P. Havlík ◽  
F. Jacquet ◽  
Boisson J-M ◽  
S. Hejduk ◽  
P. Veselý

BEGRAB_PRO.1 – a mathematical programming model for BEef and GRAssland Biodiversity PRoduction Optimisation – elaborated for analysis of organic suckler cow farms in the Protected Landscape Area White Carpathians, the Czech Republic, is presented and applied to the analysis of jointness between several environmental goods. In this way, the paper complements recent studies on jointness between commodities and non-commodities. If these goods are joint in production, agri-environmental payments must be carefully designed because they do not influence only production of the environmental good they are intended for but also the production of other environmental goods. If jointness is negative, any increase in the payment for an environmental good leads to a decrease in production of other environmental goods.


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