In this paper a metaheuristic technique called Ant Colony Optimization (ACO) is proposed to derive operating policies for a multi-purpose reservoir system. Most of the real world problems often involve non-linear optimization in their solution with high dimensionality and large number of equality and inequality constraints. Often the conventional techniques fail to yield global optimal solution...

Drought is an inevitable part of the world’s climate. It occurs in wet as well as in dry regions. Therefore, planning for drought and mitigating its impacts is essential. In this study, a hedging rule is developed using the zero/one mixed integer-programming approach. Furthermore, some procedures are introduced to ease the computational burden inherent in integer programming. Hedging rules are ...

In this paper, an improved Ant Colony Optimization (ACO) algorithm is proposed for reservoir operation. Through a collection of cooperative agents called ants, the near-optimum solution to the reservoir operation can be e ectively achieved. To apply the proposed ACO algorithm, the problem is approached by considering a nite horizon with a time series of in ow, classifying the reservoir volume t...

dam reservoirs supply potable, agricultural, and industrial water in most cities of iran. due to lack of proper operational rules or unbalanced demand versus water resources volume, (along operating time) correction in operational rules is required to fulfill current situations. hence the goal of this study is to optimize the qeshlaq dam reservoir operation rules to maximize the water release f...

ant colony optimisation (aco) algorithm and adaptive refinement mechanism are used in this paper for solution of optimization problems. many of the real engineering problems are، however، of continuous nature and finding their solution by discrete ant based algorithms requires discretisation of the decision variables in which affected the convergence and performance of the algorithm. in this pa...