A two-stage approach to agile pharmaceutical supply chain management with product substitutability in crises

Roshan, M K; Tavakkoli–Moghaddam, Reza; Rahimi, Yaser

doi:10.1016/j.compchemeng.2019.05.014

Cited by 48 publications

(25 citation statements)

References 38 publications

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“…Constraint (16) ensures that strategies A a , and Aáprevent each other for each project. Constraint (17) ensures that for each project, only one strategy must be selected if strategiesA a , and Aáexclude each other. Constraint (18) states that projects cooperate if one strategy is chosen another strategy must be chosen too.…”

Section: Mathematical Programmingmentioning

confidence: 99%

“…The proposed model for this problem is a fuzzy multi-objective nonlinear programming (FMONLP). There are a number of adopted methods to transform this model into its equivalent crisp match, from which a two-phase approach is offered [13][14][15][16][17][18][19][20]. Firstly, using an efficient method introduced by Jimenez et al, [21], the basic model is transformed into an equivalent auxiliary crisp multiobjective model.…”

Section: Proposed Uncertainty Programmingmentioning

confidence: 99%

“…Because of the risk abatement actions, a selection problem is a complex one. Therefore, they proposed a branch-and-bound algorithm and two heuristic algorithms [16,17]. Zhang and Fan [18] integrated all three key elements in project management (i.e., project expenditure, project planning horizon, and project quality).…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Approach Model to Portfolio Risk Response Strategies

Rahimi¹

2021

Risk Management

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Risk management and control of project risks have been the intrinsic characteristics of high-rise building projects in a changing built environment. In this research, a novel bi-objective model for the best mixture of projects is proposed. The first objective focuses on maximizing profits and efficiency of risk responses, and the second objective aims at minimizing project direct cost including machinery, human, and material costs to implement proper risk responses over a planning horizon under uncertainty. In this model, risks of the projects are controlled by time, quality, and cost constraints, and the most optimum risk response strategies (RRSs) are selected to eliminate or reduce the impacts of the risks. Thus, the combination of optimum projects with the best RRSs can be selected for an organizational portfolio model. Finally, to assess the solution method and the proposed model, the empirical result and sensitivity analysis are carried out. Ten large-scale high-rise building projects and their associated risks are evaluated as cases in this study.

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Section: Mathematical Programmingmentioning

confidence: 99%

Section: Proposed Uncertainty Programmingmentioning

confidence: 99%

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Fuzzy Approach Model to Portfolio Risk Response Strategies

Rahimi¹

2021

Risk Management

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“…Akbari and Karimi [20] addressed a multi-period supply chain network problem within process uncertainty for which the cost remained the same in all time periods. Jana et al [21] presented an integrated-inventory model for supply chain in an uncertain environment with conditionally perishable delays [22].…”

Section: Literature Reviewmentioning

confidence: 99%

Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty

et al. 2020

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This paper presents a multi-objective, multi-period inventory routing problem in the supply chain of perishable products under uncertain costs. In addition to traditional objectives of cost and greenhouse gas (GHG) emission minimization, a novel objective of priority index maximization has been introduced in the model. The priority index quantifies the qualitative social aspects, such as coordination, trust, behavior, and long-term relationships among the stakeholders. In a multi-echelon supply chain, the performance of distributor/retailer is affected by the performance of supplier/distributor. The priority index measures the relative performance index of each player within the supply chain. The maximization of priority index ensures the achievement of social sustainability in the supply chain. Moreover, to model cost uncertainty, a time series integrated regression fuzzy method is developed. This research comprises of three phases. In the first phase, a mixed-integer multi-objective mathematical model while considering the cost uncertainty has been formulated. In order to determine the parameters for priority index objective function, a two-phase fuzzy inference process is used and the rest of the objectives (cost and GHG) have been modeled mathematically. The second phase involves the development of solution methodology. In this phase, to solve the mathematical model, a modified interactive multi-objective fuzzy programming has been employed that incorporates experts’ preferences for objective satisfaction based on their experiences. Finally, in the third phase, a case study of the supply chain of surgical instruments is presented as an example. The results of the case provide optimal flow of products from suppliers to hospitals and the optimal sequence of the visits of different vehicle types that minimize total cost, GHG emissions, and maximizes the priority index.

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“…This is a bi-objective optimization model. For multiobjective optimization, some effective solutions were given by reference [38][39][40][41]. Next, we will analyze the model first.…”

Section: Definitionmentioning

confidence: 99%

Bi-Objective Vehicle Routing for Muck Transportation in Urban Road Networks

Guo

Wang

et al. 2020

IEEE Access

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As a consequence of expedited urban construction, large quantities of wastes are shipped every day. Because of the excessive pursuit of economic benefits by muck truck drivers and unreasonable transportation route choices, the accident rates of these drivers continue to increase. It is very important to optimize the safe transportation routing of muck trucks. In this paper, a safe transportation routing model was established to minimizes path safety risks and single driving time as the bi-objective, and two different situations for the optimal path of the model were analyzed. For the situation in which there are several short paths in the network, one of which is the path with the least safety risks, an exact algorithm, A*, was designed, and time complexity was analyzed. For the situation in which there is a single path or several shortest paths in the network but the path with the minimal path safety risks is not included in the set of shortest paths, an approximation algorithm, GA*, was designed, and time complexity and the approximation ratio were analyzed. Our experimental results demonstrated the validity of our developed model and approaches. Moreover, a case study is carried out on a real-case application related to the network in the Xi'an International Port District. INDEX TERMS muck trucks; safety transportation; vehicle routing; bi-objective programming; approximation algorithm.

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A two-stage approach to agile pharmaceutical supply chain management with product substitutability in crises

Cited by 48 publications

References 38 publications

Fuzzy Approach Model to Portfolio Risk Response Strategies

Fuzzy Approach Model to Portfolio Risk Response Strategies

Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty

Bi-Objective Vehicle Routing for Muck Transportation in Urban Road Networks

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