Scientia Iranica
Volume:28 Issue: 2, Mar-Apr 2021

An integrated coordination scheduling problem considering production and distribution in integrated energy enterprise aims at coordinating the production plan and distribution plans to eliminate the conflict between them. The research is motivated by the challenges encountered in the practice. Practice has indicated that conflicts are common existing among the plans which are made by production and distribution departments respectively. We propose a scheduling model which considers two aspects. On one hand, we try to maximize the company profit. On the other hand, we expect to minimize the difference between the separate plans and the coordinating ones. A genetic algorithm is developed to solve this problem. A case study of the largest integrated energy enterprise in China shows that once conflicts occurs in separate plans, the most effective way to adjust the separate plans from a global perspective that has strong coordinating relationships with the overall interests. The proposed model would neutralize the influence of the conflict.

Finding the most suitable transport project is one of the most important tasks in transport planning. This task gets more complicated as the sustainable criteria get involved in the process. In this paper, a new multi-criteria group decision-making method with unknown expert and attribute weights is proposed to address the sustainable transport investment selection problem. To make the method more powerful in dealing with uncertain elements, an Interval-Valued Pythagorean Fuzzy (IVPF) set is used as an attractive and useful tool to handle uncertainty. First, a generalized entropy measure under an IVPF environment is introduced, which enables the method to determine the fuzziness of the attribute values, which are expressed by Interval-Valued Pythagorean Fuzzy Numbers (IVPFNs). To determine the fuzziness of IVPFNs with identical membership and non-membership degrees, a generalized knowledge measure of the IVPFNs is also introduced. Based on this measure and considering the deviation between attribute assessments, a new optimization model is presented to obtain unknown attribute weights. In addition, based on the extension of the VIKOR method, a new algorithm is presented to determine the unknown expert weights. Finally, a real case study is considered to show the efficiency of the proposed methods.

It is widely felt that the performance evaluation in aggregate production planning provides a theoretical and practical overview. The present study aimed to evaluate the performance in the aggregate production planning. In this regard, the optimal values were determined by the multi-objective grey aggregate production planning model and the weights of the input and output indicators of the performance evaluation were characterized by the step-wise weight assessment ratio analysis (SWARA) technique. Further, the efficiency of the decision-making units was determined by the ratio efficiency dominance (RED) model. Then, the ranking of decision-making units was conducted. In the case study of automobile parts manufacturing industry in Iran, the sensitivity analysis was performed on the model and its effects were evaluated, in addition to evaluating the proposed model. The results indicated that the proposed model had a high degree of accuracy in evaluating performance compared to previous models and helps managers to make better decisions to increase the efficiency and reduce the waste of resources.

Market demand mostly possibly affected by the seller’s credit in many industrial practice, this study aims to investigate the beneficial performance of the supply chain considering the credit-linked demand under three different circumstance. We firstly develop a demand model which is a function of the trade credit period. Moreover, the supplier determines optimal trade credit period and the retailer determines optimal replenishment cycle time. Under these conditions, we first present optimal solutions for the centralized decision and the decentralized decision in Stackelberg models. Then, we develop a set of theorems to determine the optimal results. Finally, we provide a numerical example and sensitivity analysis to illustrate the efficiency of the proposed models and optimal solutions. The finding reveals that the trade credit period, replenishment cycle time, retailer’s profit, supplier’s profit and profit of the supply chain are strongly influenced by ordering cost, retail price, production cost, holding cost and the interest rate. In addition, we also find that under the condition of the trade credit, the supply chain that the supplier dominated has a better performance than that the retailer dominated. While when the supplier don’t provide the trade credit period, the result is the opposite.

The scheduling theme which determines where and when the manufacturing actions will be performed is important to perform the activities in time, efficiently and cost-effectively. In this paper, an algorithm is proposed for the solution of a flow shop scheduling problem which holds an important place in the scheduling literature. The path relinking algorithm and data mining are used together for the solution of the flow shop scheduling problem studied here. While data mining is used for globally searching the solution space, path relinking is used for local search. Data Mining is a method which is used to extract the embedded information in a cluster that includes implicit information. Path relinking is an algorithm which advances by making binary displacements in order to convert the initial solution to the guiding solution and repeats by assigning the best obtained solution within this process as to the starting point. The efficiency of the model was tested on Taillard’s flow shop scheduling problems. Consequently, it has been possible to solve the large-size problem without the considerable mathematical back round. The obtained results show that the proposed method is in the competitiveness level with the other metaheuristic methods.

Fleet assignment and crew scheduling are the most complex airline optimization problems. In this research, an optimized crew pairing set considered as an input, and a crew is chosen for assigning to each certain crew pairing. This paper presents a novel model to integrate fleet assignment and crew scheduling problems. In this model, closed routes for crews and fleet are considered simultaneously. Also, the model considers two consecutive flight legs and some characteristics such as time lag, Minimum permitted time lag and Maximum Economic time. Also, a vibration damping optimization (VDO) algorithm is introduced to find good solution for this problem in a reasonable time. Experimental design based on the Taguchi method is taken into account. To compare the proposed VDO algorithm performance, four designed test problems are solved by proposed VDO and compared with optimal solution and Particle Swarm optimization (PSO) algorithm. Then, 10 generated test problems in large scale are solved using VDO and PSO. The results show that in four designed test problems, VDO and PSO solutions have 1.62% and 2.95% gaps in average with optimal solution. Moreover, based on 10 generated test problems, in average VDO give 6.71% better solution in less time compare to PSO.

In recent years, considering the environmental competencies could help the companies/countries to successfully improve their industries regarding the sustainable development. In this study, a green open location-routing problem with simultaneous pickup and delivery (GOLRPSPD) is considered to minimize the overall costs. In addition to cost minimization, the objective function is provided the environmental competencies regarding the costs of CO2 emissions and fuel consumption. Meanwhile, in complex situation, considering the precise information could lead the results to unreliable in which considering the uncertainty theories could prevent the data loss. In this respect, this study considered the pickup and delivery demand and the travel time as probabilistic parameters. To address the issue, a robust stochastic programming approach is developed to decrease the deviations of imprecise information. Moreover, the proposed approach is implemented based on five scenarios to decide the best decision in different situations. In addition, a practical example about the multi-echelon open-location-routing model is provided to represent the feasibility and applicability of the presented robust stochastic programming approach. Finally, a comparative and sensitivity analysis is considered to indicate the validity of the proposed approach, and also represent the robustness and sensitiveness of the obtained results regarding some significant parameters, respectively.

Considering the uncertainty of the natural state and the convenience of calculation, based on the third generation prospect theory (3-PT) and grey correlation analysis (GRA), we propose a method to solve the multi-attribute decision-making (MADM) problems where the attributes are described by the linguistic intuitionistic fuzzy numbers (LIFNs). Firstly, we transform the LIFNs into the belief structure that includes identity value and belief degree. Then, the evaluation information represented by belief structure is calculated by using the 3-PT, and the prospect matrix is gotten. The alternatives are ranked by the GRA. Finally, we use the proposed method to calculate an example and compare it with other methods to prove its effectiveness and superiority.

In the present manuscript, we introduce a novel concept of T-spherical fuzzy soft set with various important operations and properties. In the field of information theory, an aggregation operator is a structured mathematical function which aggregates all the information received as input and provides a single output entity, which are found to be applicable for various important decision making applications. Some averaging aggregation operators and geometric aggregation operators (weighted, ordered and hybrid) for T-spherical fuzzy soft numbers have been proposed with their various properties. Further, utilizing the proposed aggregation operators of various types along with the properly defined score function/accuracy function, an algorithm for solving a decision making problem has been provided. The proposed methodology has also been well illustrated with the help of a numerical example. Some comparative remarks and advantages of the introduced notion of T-spherical fuzzy soft set and the proposed methodology have been listed for a better motivation and readability.

The last decade has seen an important role of container terminals in the global trade centers. By another point of view, the high cost of quay cranes on the other hand is a motivation for a set of real-world problems including of Quay Crane Assignment Problem (QCAP) and the Quay Crane Scheduling Problem (QCSP) in the hotspot of research. The main innovation of this proposal is to integrate both QCAP and QCSP to improve Quay Crane (QC) performance by an optimization goal, i.e., QCASP. A real case study in Iran has been applied to validate the proposed problem which has been formulated by a mixed integer linear programming (MILP). Due to inherent complexity of problem proposed in the real-world cases, the Teaching-Learning-Based-Optimization (TLBO) algorithm has been used to find an optimal/global solution in a reasonable time. The applied TLBO has been tuned by Taguchi method and validated in small instances in comparison with an exact method. The computational results show that our proposed TLBO algorithm can solve QCASP, especially in large size instances, successfully. Finally, a set of managerial implications has been recommended to consider the benefits of proposed methodology and algorithm regarding the real case study presented

An advantage of process incapability index over the classical process capability index is that it provides uncontaminated separation between process accuracy and process precision. However, the value of the index is hard to be obtained accurately when process parameters cannot be determined precisely. In such case fuzzy set theory can be applied to get more flexible and more sensitive information. In this article a fuzzy process incapability index is proposed when the specification limits are assumed to be type-2 fuzzy. When the process mean and variance are unknown and when the data collected is fuzzy, three fuzzy estimators are considered. A simulation study is conducted based on a TFT-LCD fuzzy process. By employing the total integral value method to the membership function of a fuzzy index, the comparisons of quality among different processes become easier.