Hybrid artificial intelligence and robust optimization for a multi-objective product portfolio problem Case study: The dairy products industry

Goli, Alireza; Zare, Hakimeh; Tavakkoli–Moghaddam, Reza; Sadeghieh, Ahmad

doi:10.1016/j.cie.2019.106090

Cited by 105 publications

(61 citation statements)

References 37 publications

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“…Since there are some major limitations in the study, future research directions can be designed accordingly. In the following, the most important recommendations are given: 1) Considering a time horizon to fulfill the demand of customers [25], 2) Extending the problem considering more real-world assumptions, such as time windows constraint [26], 3) Applying uncertainty techniques to study the uncertain nature of the parameters, such as fuzzy programming [27][28] and robust optimization [29][30], 4) Developing other algorithms to evaluate the performance of the proposed GA, such as runner root algorithm (RRA) [31], particle swarm optimization (PSO) algorithm [32] and cuckoo optimization algorithm (COA) [33]. 5) Considering other objectives (e.g., pollution minimization [34]) and applying efficient multiobjective meta-heuristic algorithms, such as non-dominated sorting genetic algorithm III (NSGA-III) [35].…”

Section: Discussionmentioning

confidence: 99%

A Capacitated Vehicle Routing Problem considering Satisfaction Level of Customers: A Genetic Algorithm

Naghshnilchi

2019

IJOR

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Capacitated vehicle routing problem (CVRP) is one of the most well-known and applicable issues in the field of transportation. It has been proved to be an NP-Complete problem. To this end, it is needed to develop a high-performance algorithm to solve the problem, particularly in large scales. This paper develops a novel mathematical model for the CVRP considering the satisfaction level of demand nodes. Then, the proposed model is validated using a numerical example and sensitivity analyses that are implemented by CPLEX solver/GAMS software. To solve the problem efficiently, a Genetic Algorithm (GA) is designed and implemented. The obtained results demonstrate that the proposed GA can yield high-quality solutions compared to exact solutions.

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Section: Discussionmentioning

confidence: 99%

A Capacitated Vehicle Routing Problem considering Satisfaction Level of Customers: A Genetic Algorithm

Naghshnilchi

2019

IJOR

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“…To model the fuzziness in artificial intelligence problems, a large body of fuzzy logic based models has been proposed [15], [55]. For example, Alireza Goli's team has proposed a range of fuzzy models to solve cell formation problem (CFP) [14], relief vehicles problem [16], transportation route planning [55], etc [56]. Kropat and Weber [57] depicted the eco-finance networks for modeling gene-expression patterns with respect to errors and uncertainty.…”

Section: B Fuzzy Logic Based Modelsmentioning

confidence: 99%

CFN: A Complex-Valued Fuzzy Network for Sarcasm Detection in Conversations

Zhang

Liu

et al. 2021

IEEE Trans. Fuzzy Syst.

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Sarcasm detection in conversation (SDC), a theoretically and practically challenging artificial intelligence (AI) task, aims to discover elusively ironic, contemptuous and metaphoric information implied in daily conversations. Most of the recent approaches in sarcasm detection have neglected the intrinsic vagueness and uncertainty of human language in emotional expression and understanding. To address this gap, we propose a complex-valued fuzzy network (CFN) by leveraging the mathematical formalisms of quantum theory (QT) and fuzzy logic. In particular, the target utterance to be recognized is considered as a quantum superposition of a set of separate words. The contextual interaction between adjacent utterances is described as the interaction between a quantum system and its surrounding environment, constructing the quantum composite system, where the weight of interaction is determined by a fuzzy membership function. In order to model both the vagueness and uncertainty, the aforementioned superposition and composite systems are mathematically encapsulated in a density matrix. Finally, a quantum fuzzy measurement is performed on the density matrix of each utterance to yield the probabilistic outcomes of sarcasm recognition. Extensive experiments are conducted on the MUStARD and the 2020 sarcasm detection Reddit track datasets, and the results show that our model outperforms a wide range of strong baselines.

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“…Kaur et al [20] formulated a restricted flow capacitated two-stage time minimization transportation problem. Goli et al [15] presented a hybrid artificial intelligence and robust optimization for a multi-objective product portfolio problem. Paul et al [35] studied effect of price-sensitive demand and default risk on optimal credit period and cycle time for a deteriorating inventory model.…”

Section: Literature Surveymentioning

confidence: 99%

Fuzzy multiple objective fractional optimization in rough approximation and its aptness to the fixed-charge transportation problem

2021

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This article presents a multiple objective fractional fixed-charge transportation problem (MFFTP) in a rough decision-making framework. A transformation procedure is modified to convert non-linear multi-objective transportation problem to its linear version. The parameters of the designed model are considered to be fuzzy. We employ separate kinds of fuzzy scale, i.e., possibility, credibility and necessity measures, to deal with the fuzzy parameters. Using the fuzzy chance-constrained rough approximation (FCRA) technique, we extract the more preferable optimal solution from our suggested MFFTP. The initial result is compared with that of the robust ranking (RR) technique. We also use the theory of rough sets for expanding as well as dividing the feasible domain of the MFFTP to accommodate more information by considering two approximations. Employing these approximations, we introduce two variants, namely, the lower approximation (LA) and the upper approximation (UA), of the suggested MFFTP. Finally, by using these models, we provide the optimal solutions for our proposedproblem. We also associate our MFFTP with a real-world example to showcase its applicability as well as performance. Our core concept of this article is that it tackles an MFFTP using two separate kinds of uncertainty and expands its feasible domain for optimal solutions. Optimal solutions of the designed model (obtained from FCRA technique) belong to two separate regions, namely, “surely region” and “possible region”. The optimal solution which belongs to the “surely region” is better (as these are minimum values) than the one in the “possible region” and other cases. An interpretation of our approach along with offers about the intended future research work are provided at last.

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Hybrid artificial intelligence and robust optimization for a multi-objective product portfolio problem Case study: The dairy products industry

Cited by 105 publications

References 37 publications

A Capacitated Vehicle Routing Problem considering Satisfaction Level of Customers: A Genetic Algorithm

A Capacitated Vehicle Routing Problem considering Satisfaction Level of Customers: A Genetic Algorithm

CFN: A Complex-Valued Fuzzy Network for Sarcasm Detection in Conversations

Fuzzy multiple objective fractional optimization in rough approximation and its aptness to the fixed-charge transportation problem

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