/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

Mathematical programming

(1962). Management Models and Industrial Applications of Linear Programming. Journal of the Operational Research Society: Vol. 13, No. 3, pp. 274-275.

https://link.springer.com/content/pdf/10.1057%2Fjors.1962.42.pdf

Management Models and Industrial Applications of Linear Programming

https://cyberleninka.org/article/n/662470.pdf

Literature review of deteriorating inventory models by key topics from 2012 to 2015

The emergence of fuzzy sets makes job-shop scheduling problem (JSSP) become better aligned with the reality. This article addresses the JSSP with fuzzy execution time and fuzzy completion time (FJSSP). We choose the classic differential evolution (DE) algorithm as the basic optimization framework. The advantage of the DE algorithm is that it uses a special evolutionary strategy of difference vector sets to carry out mutation operation. However, DE is not very effective in solving some instances of FJSSP. Therefore, we propose a novel selection mechanism augmenting the generic DE algorithm (NSODE) to achieve better optimization results. The proposed selection operator adopted in this article aims at a temporary retention of all children generated by the parent generation, and then selecting N better solutions as the new individuals from N parents and N children. Various examples of fuzzy shop scheduling problems are experimented with to test the performance of the improved DE algorithm. The NSODE algorithm is compared with a variety of existing algorithms such as ant colony optimization, particle swarm optimization, and cuckoo search. Experimental results show that the NSODE can obtain superior feasible solutions compared with solutions produced by several algorithms reported in the literature.

Solving Fuzzy Job-Shop Scheduling Problem Using DE Algorithm Improved by a Selection Mechanism

This paper analyses the multi-objective fixed-charge transportation problem (MOFCTP) using rough programming. Due to globalisation of market, the parameters of MOFCTP may not be defined precisely, so the parameters of the MOFCTP are treated as rough intervals. Expected value operator is used to convert rough MOFCTP to deterministic MOFCTP. Fuzzy programming method and linear weighted-sum method are used to obtain Pareto-optimal solution from deterministic MOFCTP. A comparative study is made between the obtained solutions extracted from the methods; and thereafter we perform a procedure to analyse the sensitive analysis of the parameters in MOFCTP. Finally, in order to show the applicability of our proposed study, an example on MOFCTP is included in this paper.

Multi-objective fixed-charge transportation problem using rough programming

Carbon and Sulfur dioxides emissions are the key issues of global warming that affects on human health. Emissions cap- and -trade policy is a key mechanism implemented in several countries to reduce the emissions. Nowadays, public gathering is restricted due to the pandemic situation caused by COVID-19. As a result, people are facing huge problems in their regular activities and lifestyle. During the lockdown periods, demands for few merchandises decrease and the deterioration rate increases. Moreover, because of the unavailability of raw materials and labours during the lockdown, shortages occur at the manufacturing company. Keeping these problems in mind, a multi-objective sustainable economic production quantity model is proposed with partially back-ordering shortages, in which the effects of sustainability are investigated. To handle the demand fluctuation throughout the current pandemic, emergency level dependent demand rate is assumed. To reduce greenhouse gases emissions and deterioration rate, investments in green technology and preservation technology efforts are used. The objectives of this study are to maximize the manufacturer’s profit and minimize the greenhouse gases emissions for producing green products. The multi-objective model is solved by utilizing the fuzzy goal programming approach. The mathematical model is illustrated by four numerical examples. The main finding of the work is that under both green and preservation technologies investments, a sustainable model with partially back-ordering shortages and lockdown level dependent demand rate decreases justifiable greenhouse gases emissions and increases the product’s greening level. The results indicate that the system profit is increased by 16.1% by investing in both preservation and green technology. Furthermore, a sensitivity analysis is performed along with some managerial insights for practitioners. Finally, the paper is ended with conclusions and future research tips.

/pdf/impacts-of-green-and-preservation-technology-investments-on-v8x4pwcd.pdf

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

This paper analyzes the study of Multiobjective Transportation Problem MOTP under the consideration of fuzzy decision variable. Usually, the decision variable in a Transportation Problem is taken a...

Multiobjective Transportation Problem Using Fuzzy Decision Variable Through Multi-Choice Programming

This paper introduces a ranking function procedure on a bi-level programming for Stackelberg game involving intuitionistic fuzzy parameters. Intuitionistic fuzzy number is considered in many real-life situations, so it makes perfect sense to address decision-making problem by using some specified intuitionistic fuzzy numbers. In this paper, intuitionistic fuzziness is characterized by a normal generalized triangular intuitionistic fuzzy number. A defuzzification method is introduced based on the proportional probability density function associated with the corresponding membership function, as well as the complement of non-membership function. Using the proposed ranking technique, a methodology is presented for solving bi-level programming for Stackelberg game. An application example is provided to demonstrate the applicability of the proposed methodology, and the achieved results are compared with the existing methods.

Bi-level Programming for Stackelberg Game with Intuitionistic Fuzzy Number: a Ranking Approach

Soft set theory has emerged recently as a new mathematical tool to handle uncertainty. Sometimes decision makers are not sure about the decision-making criteria, where soft set theory provides an i...

Sankar Kumar Roy

Papers

Multi-objective fixed-charge transportation problem using rough programming

Impacts of green and preservation technology investments on a sustainable EPQ model during COVID-19 pandemic

Multiobjective Transportation Problem Using Fuzzy Decision Variable Through Multi-Choice Programming

Bi-level Programming for Stackelberg Game with Intuitionistic Fuzzy Number: a Ranking Approach

Soft Matrix Game: A Hesitant Fuzzy MCDM Approach