This paper is devoted to the development of heuristics for the dynamic pricing problem. A discrete time model of … dynamic pricing on the fixed time horizon is proposed. It is applicable to products that satisfy two properties: 1) product … techniques. Optimal pricing policy is expressed as a function of time to expiration and inventory levels of unsold products. An …

This paper proposes a Linear Programming-based Bi-Objective time series Forecasting Algorithm that helps forecast sub …-annual short univariate time-series data. The proposed algorithm generates forecasts optimized for a pair of accuracy measures … instead of just one. The algorithm is based on the ϵ-constraint-based multi-objective optimization method. The accuracy …

Learning. Specifically, our study is framed in the context where a reference discrete optimization problem is given and there …

exploring dynamic pricing strategies of a synthetic business-to-consumer online operation and a comparative analysis of evolving … strategy-specific pricing optimization. Five price models based on market, utility, or demand information (three single and two … dynamic pricing to be superior as an input to the negotiating agent. Contributions are threefold, pointing to (a) management …

-based formulation derived by Dantzig-Wolfe decomposition and a branch-and-price algorithm. The computational experiments show that our … branch-and-price algorithm outperforms CPLEX in many cases, which solves the ordinary robust reformulation. We also examine …

study will use Teaching Learning-Based Optimization (TLBO) as the main optimizer for the problem simulation. The objective …