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1/* -*- mode: C++; c-basic-offset: 2; indent-tabs-mode: nil -*- */
2/*
3 * Main authors:
4 * Christian Schulte <schulte@gecode.org>
5 *
6 * Copyright:
7 * Christian Schulte, 2005
8 *
9 * This file is part of Gecode, the generic constraint
10 * development environment:
11 * http://www.gecode.org
12 *
13 * Permission is hereby granted, free of charge, to any person obtaining
14 * a copy of this software and associated documentation files (the
15 * "Software"), to deal in the Software without restriction, including
16 * without limitation the rights to use, copy, modify, merge, publish,
17 * distribute, sublicense, and/or sell copies of the Software, and to
18 * permit persons to whom the Software is furnished to do so, subject to
19 * the following conditions:
20 *
21 * The above copyright notice and this permission notice shall be
22 * included in all copies or substantial portions of the Software.
23 *
24 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
25 * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
26 * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
27 * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
28 * LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
29 * OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
30 * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
31 *
32 */
33
34#include <gecode/driver.hh>
35#include <gecode/int.hh>
36#include <gecode/minimodel.hh>
37
38using namespace Gecode;
39
40/// Number of warehouses
41const int n_warehouses = 5;
42/// Number of stores
43const int n_stores = 10;
44
45/// Fixed cost for one warehouse
46const int c_fixed = 30;
47
48/// Capacity of a single warehouse
49const int capacity[n_warehouses] = {
50 1, 4, 2, 1, 3
51};
52
53/// Cost for supply a store by a warehouse
54const int c_supply[n_stores][n_warehouses] = {
55 {20, 24, 11, 25, 30},
56 {28, 27, 82, 83, 74},
57 {74, 97, 71, 96, 70},
58 { 2, 55, 73, 69, 61},
59 {46, 96, 59, 83, 4},
60 {42, 22, 29, 67, 59},
61 { 1, 5, 73, 59, 56},
62 {10, 73, 13, 43, 96},
63 {93, 35, 63, 85, 46},
64 {47, 65, 55, 71, 95}
65};
66
67/// Model variants
68enum {
69 MODEL_SUMCOST, ///< Use sum as total cost
70 MODEL_LEXCOST ///< Use lexicographic cost
71};
72
73/**
74 * \brief %Example: Locating warehouses
75 *
76 * A company needs to construct warehouses to supply stores with
77 * goods. Each warehouse possibly to be constructed has a certain
78 * capacity defining how many stores it can supply. Constructing a
79 * warehouse incurs a fixed cost. Costs for transportation from
80 * warehouses to stores depend on the locations of warehouses and
81 * stores.
82 *
83 * Determine which warehouses should be constructed and which
84 * warehouse should supply which store such that overall cost
85 * (transportation cost plus construction cost) is smallest.
86 *
87 * Taken from:
88 * Pascal Van Hentenryck, The OPL Optmization Programming Language,
89 * The MIT Press, 1999.
90 *
91 * See also problem 34 at http://www.csplib.org/.
92 *
93 * Note that "Modeling and Programming with Gecode" uses this example
94 * as a case study.
95 *
96 * \ingroup Example
97 *
98 */
99template<class Script>
100class Warehouses : public Script {
101protected:
102 /// Which warehouse supplies a store
103 IntVarArray supplier;
104 /// Is a warehouse open (warehouse needed)
105 BoolVarArray open;
106 /// Cost of a store
107 IntVarArray c_store;
108public:
109 /// Actual model
110 Warehouses(const Options& opt)
111 : Script(opt),
112 supplier(*this, n_stores, 0, n_warehouses-1),
113 open(*this, n_warehouses, 0, 1),
114 c_store(*this, n_stores) {
115
116 // A warehouse is open, if it supplies to a store
117 for (int s=0; s<n_stores; s++)
118 element(*this, open, supplier[s], 1);
119
120 // Compute cost for each warehouse
121 for (int s=0; s<n_stores; s++) {
122 IntArgs c(n_warehouses, c_supply[s]);
123 c_store[s] = expr(*this, element(c, supplier[s]));
124 }
125
126 // Do not exceed capacity
127 {
128 IntSetArgs c(n_warehouses);
129 for (int w=0; w<n_warehouses; w++)
130 c[w] = IntSet(0,capacity[w]);
131 count(*this, supplier, c, IPL_DOM);
132 }
133
134 // Branch with largest minimum regret on store cost
135 branch(*this, c_store, INT_VAR_REGRET_MIN_MAX(), INT_VAL_MIN());
136 // Branch by assigning a supplier to each store
137 branch(*this, supplier, INT_VAR_NONE(), INT_VAL_MIN());
138 }
139 /// Constructor for cloning \a s
140 Warehouses(Warehouses& s) : Script(s) {
141 supplier.update(*this, s.supplier);
142 open.update(*this, s.open);
143 c_store.update(*this, s.c_store);
144 }
145};
146
147
148/// Model with cost defined as sum
149class SumCostWarehouses : public Warehouses<IntMinimizeScript> {
150protected:
151 /// Total cost
152 IntVar c_total;
153public:
154 /// Actual model
155 SumCostWarehouses(const Options& opt)
156 : Warehouses<IntMinimizeScript>(opt) {
157 // Compute total cost
158 c_total = expr(*this, c_fixed*sum(open) + sum(c_store));
159 }
160 /// Return solution cost
161 virtual IntVar cost(void) const {
162 return c_total;
163 }
164 /// Constructor for cloning \a s
165 SumCostWarehouses(SumCostWarehouses& s) : Warehouses<IntMinimizeScript>(s) {
166 c_total.update(*this, s.c_total);
167 }
168 /// Copy during cloning
169 virtual Space* copy(void) {
170 return new SumCostWarehouses(*this);
171 }
172 /// Print solution
173 virtual void
174 print(std::ostream& os) const {
175 os << "\tSupplier: " << supplier << std::endl
176 << "\tOpen warehouses: " << open << std::endl
177 << "\tStore cost: " << c_store << std::endl
178 << "\tTotal cost: " << c_total << std::endl
179 << std::endl;
180 }
181};
182
183
184/// Model with cost defined lexicographically
185class LexCostWarehouses : public Warehouses<IntLexMinimizeScript> {
186protected:
187 /// Cost for open warehouses
188 IntVar c_open;
189 /// Cost for stores
190 IntVar c_stores;
191public:
192 /// Actual model
193 LexCostWarehouses(const Options& opt)
194 : Warehouses<IntLexMinimizeScript>(opt) {
195 // Compute costs
196 c_open = expr(*this, sum(open));
197 c_stores = expr(*this, sum(c_store));
198 }
199 /// Return solution cost
200 virtual IntVarArgs cost(void) const {
201 return {c_open, c_stores};
202 }
203 /// Constructor for cloning \a s
204 LexCostWarehouses(LexCostWarehouses& s)
205 : Warehouses<IntLexMinimizeScript>(s) {
206 c_open.update(*this, s.c_open);
207 c_stores.update(*this, s.c_stores);
208 }
209 /// Copy during cloning
210 virtual Space* copy(void) {
211 return new LexCostWarehouses(*this);
212 }
213 /// Print solution
214 virtual void
215 print(std::ostream& os) const {
216 os << "\tSupplier: " << supplier << std::endl
217 << "\tOpen warehouses: " << open << std::endl
218 << "\tOpen cost: " << c_open << std::endl
219 << "\tStores cost: " << c_stores << std::endl
220 << std::endl;
221 }
222};
223
224/** \brief Main-function
225 * \relates Warehouses
226 */
227int
228main(int argc, char* argv[]) {
229 Options opt("Warehouses");
230 opt.model(MODEL_SUMCOST);
231 opt.model(MODEL_SUMCOST, "sum", "use sum of costs");
232 opt.model(MODEL_LEXCOST, "lex", "use lexicographic cost");
233 opt.solutions(0);
234 opt.iterations(10);
235 opt.parse(argc,argv);
236 switch (opt.model()) {
237 case MODEL_SUMCOST:
238 IntMinimizeScript::run<SumCostWarehouses,BAB,Options>(opt);
239 break;
240 case MODEL_LEXCOST:
241 IntLexMinimizeScript::run<LexCostWarehouses,BAB,Options>(opt);
242 break;
243 }
244 return 0;
245}
246
247// STATISTICS: example-any
248