فهرست مطالب

  • Volume:3 Issue:2, 2019
  • تاریخ انتشار: 1397/10/15
  • تعداد عناوین: 6
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  • N. Foroozesh, R. Tavakkoli, Moghaddam orcid Pages 1-10
    The assessment and selection of green supplier development programs are an intriguing and functional research subject. This paper proposes a group decision-making approach considering possibilistic statistical concepts under uncertainty to assess green supplier development programs (GSDPs) via interval-valued fuzzy sets (IVFSs). Possibility theory is employed to regard uncertainty by IVFSs. A new version of a technique for order preference by similarity to ideal solution (TOPSIS) is proposed to solve the decision problem. Possibilistic mean, standard deviation, and cube-root of skewness matrices are provided to consider relative closeness coefficients. In addition, a new version of an entropy method is introduced to obtain criteria weights under uncertainty. Finally, an illustrative example in an automobile manufacturing system is given to show the capability of the presented approach in addition to comparisons with recent fuzzy decision techniques for GSDPs.
    Keywords: Green supplier development, multi-attributes analysis, possibilistic statistical concepts, interval-valued fuzzy sets
  • Amir Farshbaf, Geranmayeh, Masoud Rabbani , Ata Allah Taleizadeh Pages 11-26
    Nowadays, coordination between members in a supply chain has become very important and beneficial to channel members. Through cooperative advertising, manufacturers and retailers can jointly participate in promotional programs. This action not only reduces the cost of advertising, but also is important to create a link with local retailers in order to increase immediate sales at the retail level. In this article, the problem of cooperative advertising and pricing decisions in a multi-product manufacturer-retailer (oligopoly market) supply chain is investigated. Stackelberg game with leadership of the manufacturer is proposed to model the problem. In order to find optimal prices and advertising expenditure, the bi-level programming approach is implemented. Solutions for the first level are determined by a genetic algorithm and best responses of retailers to the generated solutions of the manufacturer are calculated by CPLEX. Finally, numerical experiments and sensitivity analysis are conducted in order to assess the efficiency of models and solution procedures. Results show that competition will lead to a lower retail price, which is preferable from the consumers’ point of view. Also, profit of the manufacturer and retailers will decrease if competition effect increases.
    Keywords: Cooperative advertising, Pricing, Stackelberg game, genetic algorithm, Bi-level programming
  • alireza hamidieh, alireza arshadi khamseh , Bahman Naderi Pages 27-50
    Nowadays, the design of a strategic supply chain network under the incidence of disruption is regarded as one of the important priorities of governments. Supplying sustainable petrochemical products is considered as a strategic goal by managers who require reliable infrastructure design. Crisis conditions such as natural disasters and sanctions have a destructive effect on the raw materials and product flows. On the other hand, the uncertainty of input parameters affects the business environment and intensifies the condition of disruption. In the present research, a new model of resilient supply chain network is introduced in a critical condition, which consists in a combination of reactive and preventive resilient strategies. In order to deal with the parametric uncertainties caused by changes in the business environment and inadequate knowledge, an effective hybrid possibilistic-flexible robust programming method was presented. The proposed model was capable of controlling the adverse effects of uncertainties and risk-aversion level of output decisions. The extended model was analyzed in the national project of polyethylene strategic supply chain network using real data, which included the flexibility of demand, capacity, and lead time components. The results indicated that optimality and feasibility robustness were guaranteed by presenting efficiency solutions.
    Keywords: Fuzzy programming, reliability, Resilience, Robustness, Supply Chain
  • Marjan Zarea, Maryam Esmaeili , Mohsen Shaeyan, Ramin Sadeghian Pages 51-62
    This paper analyzes different pricing strategies in a two-echelon supply chain including one supplier and two retailers. The supplier and the retailers face random yield and random demand, respectively. Moreover, coordination or non-coordination of retailers in receiving the discount is investigated. Game theory is used to model and analyze the problems. The supplier as a leader of Stackelberg specifies quantity discount and an initial wholesale price. Then, retailers determine their optimal order quantity in which their profit is maximized. Finally, the supplier decides on the quantity of the input for production. Coordination of the retailers in receiving discount quantity enhances their profit and improves supply chain performance. However, the supplier gains more profit by escalating competition between customers/retailers. Numerical examples are shown to explain the results.
    Keywords: Discount Strategy, Supply Chain, Coordination, Non-coordination
  • yahia zare mehrjerdi , Mehrdad Alipoor Pages 63-76
    Firms no longer compete as autonomous entities and prefer to join in a supply chain alliance to take advantage of highly competitive business situation. Supply chain coordination has a great impact on strategic partnering and success of a firm in competitive business environment. In this paper, we propose a system dynamics simulation model for strategic partner selection in supply chain. Our model addresses a supply chain including suppliers and retailers. It presents an approach to simulating the tendency of each supplier (retailer) to select downstream (upstream) partner and the impact of their policies on the whole supply chain.
    Keywords: Supply chain coordination, strategic partnering, upstream, downstream partner selection, information sharing, system dynamics
  • Farid Najari, Mohammad Alaghebandha, Mohammad Mohammadi , Mohammad Ali Sobhanallahi Pages 77-98
    In industries machine maintenance is used in order to avoid untimely machine fails as well as to improve production effectiveness. This research regards a permutation flow shop scheduling problem with aging and learning effects considering maintenance process. In this study, it is assumed that each machine may be subject to at most one maintenance activity during the planning horizon. The objectives aim to minimize the makespan, tardiness of jobs, tardiness cost while maximizing net present value, simultaneously. Due to complexity and Np-hardness of the problem, two Pareto-based multi-objective evolutionary algorithms including non-dominated ranked genetic algorithm (NRGA) and non-dominated sorting genetic algorithm (NSGA-II) are proposed to attain Pareto solutions. In order to demonstrate applicability of the proposed methodology, a real-world application in polymer manufacturing industry is considered.
    Keywords: Permutation flow shop, Aging, Learning Effect, Maintenance, Case study