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This paper deals with the capacitated single-stage production lot sizing and scheduling problem with multiple items, setup time, stochastic demand and unrelated parallel machines. A stochastic mixed-integer linear programming model is proposed to formulate the problem. Based on the uncertain constraints, the chance constrained programming approach is used to transform them into equivalent deterministic...
This paper studies the medical resources order and distribution scheduling problem with stochastic demand. A chance-constrained programming model is proposed based on time-space network with the objective of minimizing the hospital's total operating costs. Generic algorithm is employed to solve the optimization model. The numerical test results show the good performance of the proposed method.
Stochastic modeling of globally distributed projects has become a way to evaluate the performance of teams working in different time zones. The interest in extracting and analyzing quantitative data from geographically dispersed teams has grown throughout the years as major development companies were attracted by potential benefits. We direct our attention to Follow-The-Sun (FTS), a special case of...
Based on credibility theory, this paper presents a new class of satisficing data envelopment analysis (DEA) model, in which the inputs and outputs are fuzzy variables and we adopt the concept of fuzzy chance-constrained programming and “satisficing concepts” of H. A. Simon. When the fuzzy inputs and fuzzy outputs are independent trapezoidal fuzzy variables, we transform the satisficing DEA model to...
Variable message signs (VMS), a component of intelligent transportation system (ITS) technologies, have been more and more widely applied in urban traffic management. A new model to determine optimal locations for VMS has been proposed in this paper. First, the optimal VMS location problem is formulated as a bi-level programming problem which takes into account the interaction between VMS and network-wide...
This paper considers a shortest path problem with both random and interval variables for arcs and proposes a new risk measure to synthesize both stochastic conditional Value at Risk and order relation of interval values. The proposed model defined by the hybrid conditional Value at Risk is equivalently transformed into a 0-1 mixed integer programming problem. In order to this problem analytically...
When an organization utilizes modern technology in its manufacturing process, it needs to update and upgrade its facilities repetitively by efficient ways to stay with great productivity along with efficiency so. Capital Budgeting (CB) problem is one of the most important issues in decision makings about capital in the manufacturing management. Sometimes all variables and parameters are not necessarily...
As a kind of particular stochastic programming, stochastic transportation problem attracts much attention in many fields, such as energy development, materials management, etc. In this paper, after analyzing the essence of stochastic programming and the deficiencies of existing methods, propose a quasi-linear pattern based on expectation and variance. Give a stochastic programming pattern (generalized...
Oilfield development plan is an important issue to energy exploitation. In addition to the deterministic and stochastic models brought forward in the past studies, this paper proposes a multi-objective programming model for oilfield development plan, in which parameters are fuzzy variables. In order to solve this model, we use AHP to weigh objective functions and design a hybrid intelligent algorithm...
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