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sudoku.R
# Copyright 2020, Gurobi Optimization, LLC */ # # Sudoku example. # # The Sudoku board is a 9x9 grid, which is further divided into a 3x3 grid # of 3x3 grids. Each cell in the grid must take a value from 0 to 9. # No two grid cells in the same row, column, or 3x3 subgrid may take the # same value. # # In the MIP formulation, binary variables x[i,j,v] indicate whether # cell <i,j> takes value 'v'. The constraints are as follows: # 1. Each cell must take exactly one value (sum_v x[i,j,v] = 1) # 2. Each value is used exactly once per row (sum_i x[i,j,v] = 1) # 3. Each value is used exactly once per column (sum_j x[i,j,v] = 1) # 4. Each value is used exactly once per 3x3 subgrid (sum_grid x[i,j,v] = 1) # # Input datasets for this example can be found in examples/data/sudoku*. # library(Matrix) library(gurobi) args <- commandArgs(trailingOnly = TRUE) if (length(args) < 1) { stop('Usage: Rscript sudoku.R filename\n') } # Read input file conn <- file(args[1], open='r') if(!isOpen(conn)) { cat('Could not read file',args[1],'\n') stop('Stop now\n') } linn <- readLines(conn) close(conn) # Ensure that all lines have the same length as the number of lines, and # that the character set is the correct one. # Load fixed positions in board Dim <- length(linn) board <- matrix(0, Dim, Dim, byrow = TRUE) if (Dim != 9) { cat('Input file',args[1],'has',Dim,'lines instead of 9\n') stop('Stop now\n') } for (i in 1:Dim) { line <- strsplit(linn[[i]],split='')[[1]] if (length(line) != Dim) { cat('Input line',i,'has',length(line),'characters, expected',Dim,'\n') stop('Stop now\n') } for (j in 1:Dim) { if (line[[j]] != '.') { k <- as.numeric(line[[j]]) if (k < 1 || k > Dim) { cat('Unexpected character in Input line',i,'character',j,'\n') stop('Stop now\n') } else { board[i,j] = k } } } } # Map X[i,j,k] into an index variable in the model nVars <- Dim * Dim * Dim varIdx <- function(i,j,k) {i + (j-1) * Dim + (k-1) * Dim * Dim} cat('Dataset grid:',Dim,'x',Dim,'\n') # Set-up environment env <- list() env$logfile <- 'sudoku.log' # Build model model <- list() model$modelname <- 'sudoku' model$modelsense <- 'min' # Create variable names, types, and bounds model$vtype <- 'B' model$lb <- rep(0, nVars) model$ub <- rep(1, nVars) model$varnames <- rep('', nVars) for (i in 1:Dim) { for (j in 1:Dim) { for (k in 1:Dim) { if (board[i,j] == k) model$lb[varIdx(i,j,k)] = 1 model$varnames[varIdx(i,j,k)] = paste0('X',i,j,k) } } } # Create (empty) constraints: model$A <- spMatrix(0,nVars) model$rhs <- c() model$sense <- c() model$constrnames <- c() # Each cell gets a value: for (i in 1:Dim) { for (j in 1:Dim) { B <- spMatrix(1, nVars, i = rep(1,Dim), j = varIdx(i,j,1:Dim), x = rep(1,Dim)) model$A <- rbind(model$A, B) model$rhs <- c(model$rhs, 1) model$sense <- c(model$sense, '=') model$constrnames <- c(model$constrnames, paste0('OneValInCell',i,j)) } } # Each value must appear once in each column for (i in 1:Dim) { for (k in 1:Dim) { B <- spMatrix(1, nVars, i = rep(1,Dim), j = varIdx(i,1:Dim,k), x = rep(1,Dim)) model$A <- rbind(model$A, B) model$rhs <- c(model$rhs, 1) model$sense <- c(model$sense, '=') model$constrnames <- c(model$constrnames, paste0('OnceValueInRow',i,k)) } } #Each value must appear once in each row for (j in 1:Dim) { for (k in 1:Dim) { B <- spMatrix(1, nVars, i = rep(1,Dim), j = varIdx(1:Dim,j,k), x = rep(1,Dim)) model$A <- rbind(model$A, B) model$rhs <- c(model$rhs, 1) model$sense <- c(model$sense, '=') model$constrnames <- c(model$constrnames, paste0('OnceValueInColumn',j,k)) } } # Each value must appear once in each subgrid SubDim <- 3 for (k in 1:Dim) { for (g1 in 1:SubDim) { for (g2 in 1:SubDim) { B <- spMatrix(1, nVars, i = rep(1,Dim), j = c(varIdx(1+(g1-1)*SubDim,(g2-1)*SubDim + 1:SubDim, k), varIdx(2+(g1-1)*SubDim,(g2-1)*SubDim + 1:SubDim, k), varIdx(3+(g1-1)*SubDim,(g2-1)*SubDim + 1:SubDim, k)), x = rep(1,Dim)) model$A <- rbind(model$A, B) model$rhs <- c(model$rhs, 1) model$sense <- c(model$sense, '=') model$constrnames <- c(model$constrnames, paste0('OnceValueInSubGrid',g1,g2,k)) } } } # Save model gurobi_write(model, 'sudoku.lp', env) # Optimize model result <- gurobi(model, env = env) if (result$status == 'OPTIMAL') { cat('Solution:\n') cat('----------------------------------\n') for (i in 1:Dim) { for (j in 1:Dim) { if (j %% SubDim == 1) cat('| ') for (k in 1:Dim) { if (result$x[varIdx(i,j,k)] > 0.99) { cat(k,' ') } } } cat('|\n') if (i %% SubDim == 0) cat('----------------------------------\n') } } else { cat('Problem was infeasible\n') } # Clear space rm(result, model, board, linn, env)