A particle swarm optimization for solving joint pricing and lot-sizing problem with fluctuating demand and unit purchasing cost. (English) Zbl 1205.90030

Dye, Chung-Yuan; Hsieh, Tsu-Pang

Comput. Math. Appl. 60, No. 7, 1895-1907 (2010).

Summary: We extend the classical economic order quantity model to allow for not only a function of price-dependent and time-varying demand but also fluctuating unit purchasing cost. The joint replenishment problem is subject to continuous decay and a general partial backlogging rate. The objective is to find the optimal replenishment number, time scheduling and periodic selling price to maximize the discounted total profit. An effective search procedure is provided to find the optimal solution by employing the properties derived in this paper and particle swarm optimization algorithm. Several numerical examples are used to illustrate the features of the proposed model.

MSC:

90B05	Inventory, storage, reservoirs
90C59	Approximation methods and heuristics in mathematical programming
90B06	Transportation, logistics and supply chain management
91B38	Production theory, theory of the firm

Keywords:

pricing; inventory; partial backlogging; particle swarm optimization; fluctuating cost; inflation

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