📚 docs: Improve.

Author: make-github-pseudonymous-again

README.md

@@ -1,14 +1,25 @@
 :school_satchel: [@problem-solving/knapsack](https://computational-problem-solving.github.io/knapsack)
 ==
 
+<p align="center">
+<a href="https://xkcd.com/287">
+<img src="https://imgs.xkcd.com/comics/np_complete.png" width="600">
+</a><br/>
+© <a href="https://xkcd.com">xkcd.com</a>
+</p>
+
 Knapsack problem algorithms for JavaScript.
 See [docs](https://computational-problem-solving.github.io/knapsack/index.html).
 
-> :building_construction: Caveat emptor! This is work in progress. Code may be
-> working. Documentation may be present. Coherence may be. Maybe.
+```js
+import {
+	knapsackGreedy,
+	knapsackApprox,
+} from '@problem-solving/knapsack';
 
-> :warning: The code requires `regeneratorRuntime` to be defined, for instance by importing
-> [regenerator-runtime/runtime](https://www.npmjs.com/package/regenerator-runtime).
+knapsackGreedy(n, v, w, W); // 1/2 approximation
+knapsackApprox(eps, n, v, w, W); // 1-eps approximation
+```
 
 [![License](https://img.shields.io/github/license/computational-problem-solving/knapsack.svg)](https://raw.githubusercontent.com/computational-problem-solving/knapsack/main/LICENSE)
 [![Version](https://img.shields.io/npm/v/@problem-solving/knapsack.svg)](https://www.npmjs.org/package/@problem-solving/knapsack)
@@ -27,4 +38,4 @@ See [docs](https://computational-problem-solving.github.io/knapsack/index.html).
 ## :book: References
 
   - The [knapsack problem](https://en.wikipedia.org/wiki/Knapsack_problem)
-    explained in Wikipedia.
+    explained at Wikipedia.

doc/manual/usage.md

@@ -1,18 +1,8 @@
 # Usage
 
-> :warning: The code requires `regeneratorRuntime` to be defined, for instance by importing
-> [regenerator-runtime/runtime](https://www.npmjs.com/package/regenerator-runtime).
-
-First, require the polyfill at the entry point of your application
-```js
-await import( 'regenerator-runtime/runtime.js' );
-// or
-import 'regenerator-runtime/runtime.js' ;
-```
-
-Then, import the library where needed
+Import the library where needed
 ```js
-const knapsack = await import( '@problem-solving/knapsack' ) ;
+const knapsack = await import('@problem-solving/knapsack');
 // or
-import * as knapsack from '@problem-solving/knapsack' ;
+import * as knapsack from '@problem-solving/knapsack';
 ```

src/integerValuesKnapsack.js

@@ -12,6 +12,7 @@ import {sum} from '@iterable-iterator/reduce';
  * @param {Number} W Size of the knapsack.
  * @param {Number} V Any upper bound on OPT >= 0.
  * @param {Array} m Memory buffer.
+ * @return {Number} Objective value of the optimum.
  */
 const integerValuesKnapsack = (
 	v,

src/integerValuesKnapsackUnbounded.js

@@ -15,6 +15,7 @@ import {range} from '@iterable-iterator/range';
  * @param {Number|BigInt} zero The number 0.
  * @param {Number} V Any upper bound on OPT >= 0.
  * @param {Array} m Memory buffer.
+ * @return {Number} Objective value of the optimum.
  */
 const integerValuesKnapsackUnbounded = (
 	v,

src/integerWeightsKnapsack.js

@@ -9,6 +9,7 @@ import assert from 'assert';
  * @param {Number} n Size of the problem.
  * @param {Number} W Size of the knapsack.
  * @param {Array} m Memory buffer.
+ * @return {Number} Objective value of the optimum.
  */
 const integerWeightsKnapsack = (
 	v,

src/integerWeightsKnapsackUnbounded.js

@@ -9,6 +9,7 @@ import assert from 'assert';
  * @param {Number} n Size of the problem.
  * @param {Number} W Size of the knapsack.
  * @param {Array} m Memory buffer.
+ * @return {Number} Objective value of the optimum.
  */
 const integerWeightsKnapsackUnbounded = (
 	v,

src/knapsackApprox.js

@@ -16,6 +16,8 @@ import integerValuesKnapsack from './integerValuesKnapsack.js';
  * @param {Number} n Size of the problem.
  * @param {Number} W Size of the knapsack.
  * @param {Number} P Any lower bound on OPT > 0.
+ * @return {Number} Lower bound on the objective value of a solution, that is
+ * at least 1-eps the objective value of the optimum.
  */
 const knapsackApprox = (
 	eps,

src/knapsackGreedy.js

@@ -24,6 +24,8 @@ import orderedByDecreasingUtility from './orderedByDecreasingUtility.js';
  * @param {Array} w Weights.
  * @param {Number} n Size of the problem.
  * @param {Number} W Size of the knapsack.
+ * @return {Number} Lower bound on the objective value of a solution, that is
+ * at least half the objective value of the optimum.
  */
 const knapsackGreedy = (v, w, n, W) => {
 	assert(v.length === n);

src/knapsackUnboundedGreedy.js

@@ -14,6 +14,8 @@ import orderedByDecreasingUtility from './orderedByDecreasingUtility.js';
  * @param {Array} w Weights.
  * @param {Number} n Size of the problem.
  * @param {Number} W Size of the knapsack.
+ * @return {Number} Lower bound on the objective value of a solution, that is
+ * at least half the objective value of the optimum.
  */
 const knapsackUnboundedGreedy = (v, w, n, W) => {
 	assert(v.length === n);