multi-objective model

Transportation plays a significant role in the gross domestic product and oil consumption of every nation. In our country, a combination of recent sanctions and underdeveloped rail, air, and sea transportation systems has led to an increased reliance on road transport. Unfortunately, road transport contributes significantly to the emission of greenhouse gases, particularly carbon dioxide. Nevertheless, transportation is a vital aspect of logistics, and addressing pollution in vehicle routing stands as a paramount concern within this realm.This paper introduces a model aimed at optimizing fuel consumption costs, considering various factors such as vehicle load, speed, pollution, as well as parameters like fuel and engine efficiency, incline, traffic density, wind speed and direction, air temperature, asphalt quality, and driver remuneration. Additionally, this mathematical linear mixed-integer model incorporates probabilistic demand and a distribution system involving both delivery and pickup processes, all geared towards cost minimization.By employing this model, organizations can achieve more precise cost estimates, enhanced analysis, and improved planning. Given the NP-hard nature of the problem, its resolution involves the amalgamation of two meta-heuristic algorithms: Extreme Learning Machine (ELM) and Genetic Programming (GP). Experimental results indicate that the developed hybrid algorithm offers highly accurate estimations in a remarkably short time span when compared with similar algorithms.

Due to global threats such as pandemics and wars affecting supply chains, redesigning the supplier network with circular criteria, cost reduction and proper supplier backup to reduce supply risk is a an importtant need in today's industrial society. To address this issue, this paper developed a multi-objective model with conflicting objectives to design a circular reliable supplier network considering knowledge sharing capability, backup, skills, reliable cooperation networks, cost, capacity, order allocation, and circular criteria for a modular product. The proposed model for network design simultaneously considers the following key factors: 1) circular criteria, 2) cooperation network and historical records between suppliers, 3) skills, 4) ability to share knowledge and experience, and 5) cost and backup suppliers. The model was evaluated with the numerical study of the simulated data as well as with the real data of the electro-optical camera, and it was validated with the precise method of augmented epsilon constraint method and LPmetric and the exact solution of small-scale problems, and the sensitivity analysis was also performed.; Therefore, first a modular product was selected and the number of modules was determined by clustering. Then, the parameters and variables were determined and after formulating and solving the model, the model was validated and the results, teams and optimal order allocation were determined. From the results of solving the model with artificial data, the main team (1, 2, 3, 4 and 15) and the support team (4, 8 and 9) were obtained. Also, according to the results of solving the model with real data, the main team (1, 2, 3, 8, 9 and 10) and the support team (4) were obtained. The results showed that, based on all the assumptionsو this approach, suggests the network of optimal circular reliable suppliers in two main and supporting groups with the lowest cost, the most knowledge sharing and reliability and circular criteria. The results are in line with the needs of modern industrial society. At the end, suggestions for future research were presented.

 Optimizing the negative balance of the financial portfolio of branches by observing the limits defined in the banking system of Iran.

 In recent years, several models have been proposed for the investment portfolio. In banks, Fundraising operations are carried out in parallel with investments. Attracting deposits and repaying loans are the main pillars of investment and form the basis of the resource and expenditure portfolio in the bank. In this research, a multi-objective planning model is designed to maximize returns and minimize risk.

 The approach of the problem is such that by taking administrative and personnel costs and interest rates on deposits and facilities and exchange rates of the domestic market can offer a variety of portfolios. The branches select the appropriate portfolio as the goal and work plan according to their requirements.

 Due to the nature of the problem, which is hard nonlinear, the model is solved using NSGA-II evolutionary algorithm. The output of solving the problem is a set of optimal solutions on the Pareto frontier. Each of the portfolios is a strategic choice for the decision-maker, according to the level of return and risk.

Recently, university courses time tabling problem has been attended as a main issue by most universities and educational departments. In this paper, a bi-objective model is proposed to formulate a university courses time tabling problem which aims to minimize the cost of assigning courses to professors and classes during time horizon and maximize professorschr('39') satisfaction through minimizing their total idle time, simultaneously. Furthermore, despite of previous similar works in this area in which predefined values are considered as the assignmentchr('39') cost coefficients, in this paper, for the first time, an analytical hierarchy process (AHP) approach is used to calculate these coefficients which enables educational departments to attend various criteria in considering assignment cost coefficients. Finally, to evaluate the efficiency of the proposed model, a real case study in industrial engineering faculty of Bu-Ali Sina University is done.

For powerful manufacturing firms, one of the important factors for survival in today's competitive environment is decreasing production costs. Materials and equipment supplied play an important role in supply chain management and production facilities location, have a significant impact on supply chain design from the perspective of transportation and distribution planning in logistics decisions of the company. The purpose of this study is to provide an integrated model for supplier selection, quota allocation and production facility location problems in a multi - period and multi - product supply chain by considering economic goals, network reliability and evaluation of selected suppliers. In this regard, a mixed integer programming model has been developed and solved for small size problems by an exact method. Since the proposed problem is NP-hard, a Multi-Objective Vibration Damping Optimization (MOVDO) algorithm is proposed by introducing criteria for examining the results to solve large-scale problems. Numerical results show that the MOVDO algorithm reduces the problem solving time and provides near-optimal solutions with a small percentage difference compared to the exact method, which is also good in the quality of the response criterion.