
The study of cuckoo optimization algorithm for production planning problem
Constrained Nonlinear programming problems are hard problems, and one of...
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Simplified Swarm Optimization for BiObjection Active Reliability Redundancy Allocation Problems
The reliability redundancy allocation problem (RRAP) is a wellknown too...
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Capital flow constrained lot sizing problem with loss of goodwill and loan
We introduce capital flow constraints, loss of good will and loan to the...
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A Stochastic Biomass Blending Problem in Decentralized Supply Chains
Blending biomass materials of different physical or chemical properties ...
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A bilevel approach for optimal contract pricing of independent dispatchable DG units in distribution networks
Distributed Generation (DG) units are increasingly installed in the powe...
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A feasibility pump algorithm embedded in an annealing framework
The feasibility pump algorithm is an efficient primal heuristic for find...
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Developing a Mathematical Negotiation Mechanism for a Distributed Procurement Problem and a Hybrid Algorithm for its Solution
Considering the players' bargaining power, designing a bilevel programming model is suitable to reflect the hierarchical nature of the decisionmaking process. In this paper, typical negotiation components perfectly match with the mathematical model and its solution procedure. For this purpose, a mathematical negotiation mechanism is designed to minimize the negotiators' costs in a distributed procurement problem at two echelons of an automotive supply chain. The buyer's costs are procurement cost and shortage penalty in a oneperiod contract. On the other hand, the suppliers intend to solve a multiperiod, multiproduct production planning to minimize their costs. Such a mechanism provides an alignment among suppliers' production planning and order allocation, also supports the partnership with the valued suppliers by taking suppliers' capacities into account. Such a circumstance has been modeled via bilevel programming, in which the buyer acts as a leader, and the suppliers individually appear as followers in the lower level. To solve this nonlinear bilevel programming model, a hybrid algorithm by combining the particle swarm optimization algorithm with a heuristic algorithm based on A search is proposed. In this algorithm, a heuristic algorithm based on A search is embedded to solve the mixedinteger nonlinear programming subproblems for each supplier according to the received variable values determined by PSO system particles.
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