This paper presents a method, called multiple constant multiplier trees (MCMTs), for producing optimized reconfigurable hardware implementations of vector products. An algorithm for generating MCMTs has been developed and implemented, which is based on a novel representation of common sub-expressions in constant data patterns. Our optimization framework covers a wider solution space than previous approaches; it also supports exploitation of full and partial run-time reconfiguration as well as technology-specific constraints, such as fan out limits and routing. We demonstrate that while distributed arithmetic techniques require storage size exponential in the number of coefficients, the resource utilization of MCMTs usually grows linearly with problem size. MCMTs have been implemented in Xilinx 4000 and Virtex FPGAs, and their size and speed efficiency are confirmed in comparisons with Xilinx LogiCore and ASIC implementations of FIR filter designs. Preliminary results show that the size of MCMT circuits is less than half of that of comparable distributed arithmetic cores.