Browsing by Subject "Mixed integer linear programming"

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    Disassembly line balancing with sequencing decisions: A mixed integer linear programming model and extensions
    (Elsevier Ltd, 2019) Edis E.B.; Ilgin M.A.; Edis R.S.
    Due to the acceleration of technological developments and shortening of product life cycles, product recovery has gained great importance in recent years. Disassembly line balancing (DLB) problem is one of the most important problems encountered during disassembly operations in product recovery. In this study, a single model and complete DLB problem with balancing issues, hazardousness of parts, demand quantities and direction changes is considered. Majority of DLB studies in the literature solve this problem using heuristics or metaheuristics which do not guarantee the optimality. Although a few studies present mathematical formulations for some variants of this problem, they prefer to solve the problem by using heuristics or metaheuristics due to the non-linear structure and combinatorial nature of the problem. In this study, a generic mixed integer linear programming (MILP) model is developed for the investigated problem and its performance is tested through a series of benchmark instances. The computational results demonstrate that the proposed MILP model is able to solve test instances with up to 30 tasks. Hence, it can effectively be utilized to evaluate the optimality performance of DLB approaches. Moreover, several extensions on the MILP model regarding to line balancing, hazardousness and demand of parts and direction changes are proposed and their effects are analyzed through computational studies. © 2019 Elsevier Ltd
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    A new mixed-integer linear programming formulation and particle swarm optimization based hybrid heuristic for the problem of resource investment and balancing of the assembly line with multi-manned workstations
    (Elsevier Ltd, 2019) Şahin M.; Kellegöz T.
    Resource investment and balancing problem of an assembly line with parallel multi-manned workstations can be defined as the assignment of tasks to reduce the cost of the line, which includes the cost of opened workstations and required renewable resources. Although mentioned problem has been commonly occurred in industrial environment that produce large scale products in high volumes, there have been restricted number of studies in the literature about this field. This article proposes a new mixed-integer linear programming approach that can be used in solving small size instances of the problem. In addition, a new hybrid method has been developed to solve larger scale instances by combining particle swarm optimization algorithm with a special constructive heuristic. In the constructive heuristic, serial schedule generation scheme widely used in solving resource constrained project scheduling problems has been adapted to resource investment problem with some modifications. Proposed metaheuristic has been compared against a tabu search and cuckoo search algorithm taken from the assembly line balancing literature. Many precedence diagrams commonly used in solving various assembly line balancing problems in the literature, have been used to generate test instances for the considered problem type. After solving these test instances using each solution methods, it has been observed that the proposed hybrid metaheuristic yielded the solutions, which have acceptable deviations from the lower bounds. © 2019 Elsevier Ltd