فهرس المقالات Combinatorial optimization

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  1 - An integrated crew scheduling problem considering reserve crew in air transportation: Ant colony optimization algorithm
  Saeed Saemi Alireza Rashidi Komijan Reza Tavakkoli-Moghaddam Mohammad Fallah
  10.22094/joie.2022.1934788.1885
  A Crew Scheduling Problem (CSP) is a highly complex airline optimization problem, which includes two sub-problems, namely Crew Rostering Problem (CRP) and Crew Pairing Problem (CPP). Solving these problems sequentially may not lead to an optimal solution. To overcome th أکثر

  A Crew Scheduling Problem (CSP) is a highly complex airline optimization problem, which includes two sub-problems, namely Crew Rostering Problem (CRP) and Crew Pairing Problem (CPP). Solving these problems sequentially may not lead to an optimal solution. To overcome this shortcoming, the present study introduces a new bi-objective formulation for the integrating CPP and CRP by considering the reserve crew with the objectives of crew cost minimization and crew reserve maximization. The integrated model generates and assigns pairings to a group of crew members by taking into account the rules and regulations about employing the manpower (i.e., crew member) and crew reservation in order to reduce flight delays or even cancellations due to the unexpected disruptions. An Ant Colony Optimization (ACO) algorithm is used to solve the considered problem. To justify the efficiency of this proposed algorithm in solving the presented model, different test problems are generated and solved by ACO and GAMS. The computational results indicate that solutions obtained by the proposed ACO algorithm have a 2.57% gap with the optimal solutions reported by GAMS as optimization software on average and significantly less CPU time for small-sized problems. Also, ACO obtains better solutions in significantly shorter CPU time for large-sized problems. The results indicate the efficient performance of the proposed algorithm in solving the given problems. تفاصيل المقالة
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  2 - A Simulated Annealing Algorithm for Multi Objective Flexible Job Shop Scheduling with Overlapping in Operations
  Mehrzad Abdi Khalife Babak Abbasi Amirhossein Kamali Dolat abadi
  In this paper, we considered solving approaches to flexible job shop problems. Makespan is not a good evaluation criterion with overlapping in operations assumption. Accordingly, in addition to makespan, we used total machine work loading time and critical machine work أکثر

  In this paper, we considered solving approaches to flexible job shop problems. Makespan is not a good evaluation criterion with overlapping in operations assumption. Accordingly, in addition to makespan, we used total machine work loading time and critical machine work loading time as evaluation criteria. As overlapping in operations is a practical assumption in chemical, petrochemical, and glass industries, we used simulated annealing algorithm for multi-objective flexible job shop scheduling problem with overlapping in operations to find a suitable solution. To evaluate performance of the algorithm, we developed a mixed integer linear programming model, and solved it with the classical method (branch and bound). The results showed that in small size problems, the solutions of the proposed algorithm and the mathematical model were so close, and in medium size problems, they only had lower and upper bounds of solution and our proposed algorithm had a suitable solution. We used an experimental design for improving the proposed algorithm. تفاصيل المقالة
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  3 - A new metaheuristic genetic-based placement algorithm for 2D strip packing
  Jaya Thomas Narendra S. Chaudhari
  Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The أکثر

  Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. In this paper, we give a hybrid approach which combined genetic encoding and evolution scheme with the proposed placement approach. Such a combination resulted in better population evolution and faster solution convergence to optimal. The approach is subjected to a comprehensive test using benchmark instances. The computation results validate the solution and the effectiveness of the approach. تفاصيل المقالة
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  4 - Cuckoo search via Lévy flights for the capacitated vehicle routing problem
  Jon Henly Santillan Samantha Tapucar Cinmayii Manliguez Vicente Calag
  For this paper, we explored the implementation of the cuckoo search algorithm applied to the capacitated vehicle routing problem. The cuckoo search algorithm was implemented with Lévy flights with the 2-opt and double-bridge operations, and with 500 iterations fo أکثر

  For this paper, we explored the implementation of the cuckoo search algorithm applied to the capacitated vehicle routing problem. The cuckoo search algorithm was implemented with Lévy flights with the 2-opt and double-bridge operations, and with 500 iterations for each run. The algorithm was tested on the problem instances from the Augerat benchmark dataset. The algorithm did not perform well on the problem instances, save for a select few on which the algorithm achieved the close to near-optimal result and one on which the algorithm achieved the optimal result. Increasing the number of iterations for each run of the algorithm on the two large-scale problem instances led to obtaining solutions closer to the optimal solution compared to the ones obtained with fewer number iterations. This gives an idea that the larger the problem instance becomes, the slower the algorithm converges to the optimal solution. Several other factors may also have contributed to the overall performance of the algorithm. Regardless of its performance, the algorithm was able to obtain routes that satisfied the constraints of the capacitated vehicle routing problem. The potential of the cuckoo search algorithm in solving combinatorial problems is demonstrated in this study in which the performance of the algorithm on routing problems was explored. تفاصيل المقالة