scholarly journals Sewer Networks Optimization Using Cellular Automata

2013 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Maryam Rohani ◽  
Mohammad Hadi Afshar
Keyword(s):  
Cellular Automata ◽  
Alternative Methods ◽  
Hybrid Cellular Automata ◽  
Total Cost ◽  
Sewer Network ◽  
Network Problems ◽  
Decision Variables ◽  
Two Stages ◽  
Operational Constraints ◽  
Sewer Networks

The Hybrid Cellular Automata (HCA) method is used in this paper for the optimal design of sewer network problems with the fixed layout. The HCA method decomposes the problem into two sub-problems with considering the pipe diameters and nodal cover depths as decision variables. Two stages are solved iteratively for determining the decision variables in a manner to minimize the total cost of the sewer network subject to the operational constraints. The HCA method is used to optimally solve three benchmark examples with different sizes and the results are presented and compared to those of the existing methods. The results indicate that the HCA method is more efficient and effective than the alternative methods.

GA–GHCA model for the optimal design of pumped sewer networks

2015 ◽  
Vol 42 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Maryam Rohani ◽  
Mohammad Hadi Afshar
Keyword(s):  
Genetic Algorithm ◽  
Optimal Design ◽  
Cellular Automata ◽  
Hybrid Model ◽  
Alternative Methods ◽  
Hybrid Cellular Automata ◽  
Network Characteristics ◽  
Sewer Network ◽  
Considerable Success ◽  
Sewer Networks

In this paper, a hybrid model, GA–GHCA, composed of the genetic algorithm (GA) and the general hybrid cellular automata (GHCA) is proposed for the efficient and effective optimal design of pumped sewer networks with fixed layout. The GHCA model was recently introduced by the authors with considerable success for the optimal design of sewer networks. Two alternative versions of the GA–GHCA model are proposed. In the first approach, the pump locations and the corresponding pumping heads are decided by the GA model, while the diameter and nodal cover depths of the network pipes are optimally determined by the GHCA model considering the predefined pump locations and their pumping heights defined by the GA. In the second model, however, only the pump locations are decided by the GA model and for each GA individual, the network characteristics including the pipe diameters, pipe nodal cover depths, and the pumping heights at the predefined locations are determined by the GHCA model. The proposed GA–GHCA model is tested against a benchmark example of pumped sewer network and the results are presented and compared to those of the existing methods. The results indicate that the proposed method is more efficient and effective than alternative methods for the optimal design of pumped sewer networks.

Optimizing operations in 3‐D land seismic surveys

Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1818-1826 ◽  
Author(s):  
Douglas J. Morrice ◽  
Astrid S. Kenyon ◽  
Christian J. Beckett
Keyword(s):  
Minimum Cost ◽  
Seismic Survey ◽  
Production Parameter ◽  
Microsoft Excel ◽  
Trade Off ◽  
Seismic Surveys ◽  
Total Cost ◽  
Decision Variables ◽  
Conduct Sensitivity Analysis ◽  
Operational Constraints

We formulate and solve a mathematical programming optimization model to find a minimum cost solution for an orthogonal split‐spread design in a 3‐D land seismic survey. The model contains decision variables on source and receiver location spacings, the amount of receiver equipment, and the production rate of the seismic crews. The model includes operational constraints for source and receiver movements. It also includes geophysical constraints for fold coverage, offset, and azimuth. To demonstrate the efficacy of the model, we include an example and solve it using the nonlinear optimization solver in Microsoft Excel. The model results demonstrate the classic trade‐off between source and receiver points to satisfy the geophysical requirements. In addition, we conduct sensitivity analysis on an important production parameter: the maximum number of source points that can be shot per day. We show that although changes to this parameter do not impact the decision variables, such changes do have a significant effect on the total cost of the survey.

scholarly journals Inventory and preservation investment for deteriorating system with stock-dependent demand and partial backlogged shortages

2020 ◽  
pp. 38-38
Author(s):  
Nita Shah ◽  
Kavita Rabari ◽  
Ekta Patel
Keyword(s):  
Sensitivity Analysis ◽  
Total Cost ◽  
Deterioration Rate ◽  
Preservation Technology ◽  
Decision Variables ◽  
Stock Dependent Demand ◽  
Rate Controlled ◽  
Financial Losses ◽  
Constant Deterioration ◽  
Dependent Demand

Our model deals with the stock-dependent demand as exhibiting huge volume of commodities leads to more costumers and augment the trading of the goods. As some goods like vegetables, fruits, medicines deteriorate after a period of time, resulting in economical and financial losses, we took this factor into consideration and included a constant deterioration rate, controlled by suitable preservation technologies. Preservation technology investments are made for the valuable business as it helps to decrease the rate of deterioration. Our model allows shortages, and back-ordering is permissible to manage the loss that occurs due to perishable objects and shortages. The objectives are to find the optimal cycle time, preservation technology cost, and positive inventory time. The paper also proves the convexity of total cost through graphs with respect to decision variables. A sensitivity analysis of decision variables with respect to different inventory parameters is carried out.

Preemptive scheduling with transportation delays between machines

2020 ◽  
Vol 15 (3) ◽  
pp. 829-847
Author(s):  
Ryma Zineb Badaoui ◽  
Mourad Boudhar ◽  
Mohammed Dahane
Keyword(s):  
Linear Programming ◽  
Neighborhood Search ◽  
Preemptive Scheduling ◽  
Scheduling Problem ◽  
Programming Formulation ◽  
Content Type ◽  
Decision Variables ◽  
Linear Programming Formulation ◽  
Local Search Strategy ◽  
Two Stages

Purpose This paper studies the preemptive scheduling problem of independent jobs on identical machines. The purpose of this paper is to minimize the makespan under the imposed constraints, namely, the ones that relate the transportation delays which are required to transport a preempted job from one machine to another. This study considers the case when the transportation delays are variable. Design/methodology/approach The contribution is twofold. First, this study proposes a new linear programming formulation in real and binary decision variables. Then, this study proposes and implements a solution strategy, which consists of two stages. The goal of the first stage is to obtain the best machines order using a local search strategy. For the second stage, the objective is to determine the best possible sequence of jobs. To solve the preemptive scheduling problem with transportation delays, this study proposes a heuristic and two metaheuristics (simulated annealing and variable neighborhood search), each with two modes of evaluation. Findings Computational experiments are presented and discussed on randomly generated instances. Practical implications The study has implications in various industrial environments when the preemption of jobs is allowed. Originality/value This study proposes a new linear programming formulation for the problem with variable transportation delays as well as a corresponding heuristic and metaheuristics.

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