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This paper develops a decision making framework for mid-term scheduling problems of the large industrial consumers. The proposed approach is based upon the recently introduced class of stochastic programming problems, established by the concept of second-order stochastic dominance (SSD). In this paper, it is assumed that the electricity price and the rate of availability (unavailability) of the generating unit (forced outage rate) are the sources of uncertainty in the decision-making problem. In the developed SSD-constrained stochastic programming problem, the consumer risk is managed by minimization of the pool procurement, as the objective function, and economic issues (e.g., cost minimization) are considered in the SD constraint. Furthermore, while most approaches optimize the cost subject to an assumed demand profile, our method enforces the electricity consumption to follow an optimum profile for mid-term time scheduling, i.e., three months (12 weeks), so that the total production will remain constant. Simulation results for a typical cement factory (as an industrial consumer) and comparison to a mean-risk approach with CVaR risk measure, revealed the interesting results and benefits of the proposed approach.